Analysis of the effect of the Deprivations factors from the English government over the English Housing market prices

Introduction

The current project was made during and for the course Data Science for Business Analytics teached by Professor Vatter at HEC Lausanne.

To better understand the choice of the topic, it was motivated by a large interest in the real estate market. Sadly, data from the swiss market is quite hard to find and I therefore decided to turn myself to the UK.

One of the main decision point was the discovery of the IMD (Indice of Multiple Deprivation) made by the UK government to rank different regional places in term of Deprivation. Moreover, the HM Land Registry opened their price sales data to the public for non-commercial use, which is perfect in the actual case.

Those discoveries gave me the ability to have multiple data sources letting me work on this topic.

The Research question that will be discussed and answered in this paper are:

• Are the housing prices linked to the the Employment, Criminality, Income and Health deprivation levels of the different geographical regions?
• Are the mean, median prices and overall price range in an area linked to the IMD?
• Is there a difference in the type of housings depending on the deprivation levels?
• Are we building more in the less deprived area or in the most deprived?

Before diving into the project in itself, here is a map of the UK LSOA (Lower super output area) that will be used in the project with their ranking in terms of Deprivation, places ranked low are highly deprived and places ranked high are lowly deprived.

Data

This section is dedicated to present the data sets used and tidy them.

Sources

To make this project, 3 data sets were used:

• 1. The priced paid data
• 2. The IMD data
• 3. The Postcode data

The 2 firsts data sets comes from the UK government online website while the third one comes from a web developer who made it from various sources before all cited at the bottom of the page.

Let’s now have a look at each dataset

Priced Paid Data

We will first start by having a look at the housing price data. As you can see, the first thing that has to be done is the naming of the variables from what we know on the website. After naming we have the following 16 variables:

Now let’s speak about the data points and what we will keep

#> tibble [992,818 x 16] (S3: tbl_df/tbl/data.frame)
#>  $ Unique_transaction_code: chr [1:992818] "{8F1B26BD-60CA-53DB-E0"..
#>  $ Price                  : int [1:992818] 221950 246995 244950 139..
#>  $ Date                   : chr [1:992818] "2019-04-26 00:00" "201"..
#>  $ Postcode               : chr [1:992818] "TS17 5FF" "TS15 9ZH" ""..
#>  $ Housing_type           : chr [1:992818] "D" "D" "T" "S" ...
#>  $ New_or_old             : chr [1:992818] "Y" "Y" "Y" "Y" ...
#>  $ Freehold_Leasehold     : chr [1:992818] "F" "F" "F" "F" ...
#>  $ Street_number          : chr [1:992818] "3" "16" "13" "40" ...
#>  $ NA                     : chr [1:992818] "" "" "" "" ...
#>  $ Street                 : chr [1:992818] "CARRAWBURGH ROAD" "GRE"..
#>  $ Locality               : chr [1:992818] "INGLEBY BARWICK" "" """..
#>  $ Town_City              : chr [1:992818] "STOCKTON-ON-TEES" "YAR"..
#>  $ District               : chr [1:992818] "STOCKTON-ON-TEES" "STO"..
#>  $ County                 : chr [1:992818] "STOCKTON-ON-TEES" "STO"..
#>  $ NA                     : chr [1:992818] "A" "A" "A" "A" ...
#>  $ NA                     : chr [1:992818] "A" "A" "A" "A" ...
#> NULL

This dataset contains 992’818 observations, each one being a sale that occurred in the UK in 2019. As you can see, there are 3 variables that were called NA, this is due to the fact that I was unable during the search of their meaning to find what they were meaning since the first one is empty the whole time and the two others I sadly wasn’t able to fin the answer on their exact meaning for the moment (time of HW4).

We have 16 variables with the most important:

• Unique_transaction_code Unique code for each sale
• Date Which is the date of the day the sale occured
• Postcode Postcode of the place of the building
• Price Price of the exchange
• Housing_type Type of housing with D = Detached, S = Semi-Detached, T = Terraced, F = Flats/Maisonettes, O = Other
• New_or_old Telling us if the construction is new (Y) or old (N)
• Freehold_Leasehold Specifying if the building was contains the land (Freehold) or not (Leasehold)
• Street_number Street number
• Street Name of the street
• Locality Name of the locality
• Town_City Name of the city
• District Name of the district

For the analysis we will only keep the Unique_transaction_code,the Postcode, the Price, the Housing_type, the New_or_old, the Freehold_Leasehold adn the Date. Since those variable will either be needed for the analysis of will give the ability to answer further questions or explanation of the results. While locality and street names would not grant any information to resolve the research questions.

IMD Data

We will now look at the IMD data, this data is for the year 2019 too. Compared to the Priced paid data, this one is already quite usable and do not need as much tidying as the first one, the first thing to do is to rename the variables to present them:

#> tibble [32,844 x 20] (S3: tbl_df/tbl/data.frame)
#>  $ LSOA_code                : chr [1:32844] "E01000001 " "E0100000"..
#>  $ LSOA_name                : chr [1:32844] "City of London 001A ""..
#>  $ Local_Authority_code     : chr [1:32844] "E09000001 " "E0900000"..
#>  $ Local_Authority_Name     : chr [1:32844] "City of London " "Cit"..
#>  $ IMD_rank                 : chr [1:32844] "29 199 " "30 379 " "1"..
#>  $ IMD_decile               : num [1:32844] 9 10 5 3 5 3 2 3 3 3 ...
#>  $ Income_rank              : chr [1:32844] "32 831 " "29 901 " "1"..
#>  $ Income_decile            : num [1:32844] 10 10 6 2 5 2 2 3 3 3 ...
#>  $ Employment_rank          : chr [1:32844] "32 742 " "31 190 " "1"..
#>  $ Employment_decile        : num [1:32844] 10 10 5 3 7 4 2 4 6 5 ...
#>  $ Skill_rank               : chr [1:32844] "32 842 " "32 832 " "2"..
#>  $ Skill_decile             : num [1:32844] 10 10 9 4 6 7 4 6 7 4 ...
#>  $ Health_Deprivation_rank  : chr [1:32844] "32 113 " "29 705 " "1"..
#>  $ Health_Deprivation_decile: num [1:32844] 10 10 6 6 7 5 4 3 5 6 ...
#>  $ Crime_rank               : chr [1:32844] "32 662 " "32 789 " "2"..
#>  $ Crime_decile             : num [1:32844] 10 10 9 10 6 2 4 2 1 3 ..
#>  $ Barrier_to_Housing_Rank  : chr [1:32844] "7 319 " "11 707 " "2 "..
#>  $ Barrier_to_Housing_Decile: num [1:32844] 3 4 1 1 1 1 1 1 1 1 ...
#>  $ Living_Environment_rank  : chr [1:32844] "7 789 " "13 070 " "4 "..
#>  $ Living_Environment_Decile: int [1:32844] 3 4 2 3 4 4 3 3 1 2 ...
#> NULL

This datast contains 32’844 observations for 22 variables:

• LSOA_code Code of the LSOA (Lower Layer Super Output Area)
• LSOA_name Name of the LSOA
• IMD_rank & IMD_decile Ranking and decile of each LSOA for IMD
• Income_rank & Income_decile Ranking and decile of each LSOA for Income
• Employment_rank & Employment_decile Ranking and decile of each LSOA for Employment
• Crime_rank & Crime_decile Ranking and decile of each LSOA for Crime
• Living_Environment_rank & Living_Environment_Decile Ranking and decile of each LSOA for Living Environment
• Health_Deprivation_Rank & Health_Deprivation_Decile Ranking and decile of each LSOA for Helth deprivation
• Skill_rank & Skill_DecileRanking and decile of each LSOA for Skill
• Barrier_to_Housing_rank & Barrier_to_Housing_Decile Ranking and decile of each LSOA for Barrier to housing
• Education & Education1 Ranking and decile of each LSOA for Education
• Local_Authority_Name & Local_Authority_code Name and code of the local authority

For the analysis we will keep the LSOA_code & LSOA_name to be able to do the link with the rest of the data and for answering the research questions, we need to have the rank and decile for IMD , Income, Employment, Crime, Health Deprivation & Skill.

As you can see, we have an issue with the data type of the ranks and decides, we therefore need to change their type as numeric to be able to use them easily which gives us the following:

#> 'data.frame':    32844 obs. of  14 variables:
#>  $ LSOA_code                : chr  "E01000001" "E01000002" "E01000"..
#>  $ LSOA_name                : chr  "City of London 001A " "City of"..
#>  $ IMD_rank                 : int  29199 30379 14915 8678 14486 725..
#>  $ IMD_decile               : int  9 10 5 3 5 3 2 3 3 3 ...
#>  $ Income_rank              : int  32831 29901 18510 6029 14023 626..
#>  $ Income_decile            : int  10 10 6 2 5 2 2 3 3 3 ...
#>  $ Employment_rank          : int  32742 31190 15103 7833 21692 114..
#>  $ Employment_decile        : int  10 10 5 3 7 4 2 4 6 5 ...
#>  $ Crime_rank               : int  32662 32789 29363 31059 18848 49..
#>  $ Crime_decile             : int  10 10 9 10 6 2 4 2 1 3 ...
#>  $ Health_Deprivation_rank  : int  32113 29705 17600 17907 21581 16..
#>  $ Health_Deprivation_decile: int  10 10 6 6 7 5 4 3 5 6 ...
#>  $ Skill_rank               : int  32842 32832 26386 12370 17511 20..
#>  $ Skill_decile             : int  10 10 9 4 6 7 4 6 7 4 ...
#> NULL

Postcodes Data

Finally we have the Postcodes Data, which is there only to give the ability to link the other two tables together.

To gain time, and avoid describing the 2,634,087 observations and 49 variables since only a few will be really interesting, we will go straight to the few we are going to keep.

So here is an insight to the kept table:

#> tibble [2,634,087 x 2] (S3: tbl_df/tbl/data.frame)
#>  $ Postcode : chr [1:2634087] "AB1 0AA" "AB1 0AB" "AB1 0AD" "AB1 0"..
#>  $ LSOA_code: chr [1:2634087] "S01006514" "S01006514" "S01006514" "..
#> NULL

This table, once wrangled contains only the Postcodeand the LSOA code so we are able to link the 2 other one together because Postcodes is a unique value in this table while it could be multiple times in Price paid data and the LSOA code is multiple time in this table and is a unique value in the IMD data.

Joining Data together

Now that we talked about each dataset we can linked them all together for the rest of the project.

We will do this in 2 parts :

• 1. Linking the Postcode data to the Price paid data to have the LSOA code in the resulting table
• 2. Using the newly added LSOA code to link the IMD table to the Price paid data
     

We then have a table like the one seen right under, I am only outputting the firsts 1000 rows since 992’818 observations is way too much :

#> tibble [992,818 x 21] (S3: tbl_df/tbl/data.frame)
#>  $ Unique_transaction_code  : chr [1:992818] "{8F1B26BD-60CA-53DB-"..
#>  $ Postcode                 : chr [1:992818] "TS17 5FF" "TS15 9ZH""..
#>  $ Price                    : int [1:992818] 221950 246995 244950 1..
#>  $ Housing_type             : chr [1:992818] "D" "D" "T" "S" ...
#>  $ New_or_old               : chr [1:992818] "Y" "Y" "Y" "Y" ...
#>  $ Freehold_Leasehold       : chr [1:992818] "F" "F" "F" "F" ...
#>  $ Date                     : chr [1:992818] "2019-04-26 00:00" "2"..
#>  $ LSOA_code                : chr [1:992818] "E01033474" "E0101223"..
#>  $ LSOA_name                : chr [1:992818] "Stockton-on-Tees 023"..
#>  $ IMD_rank                 : int [1:992818] 28901 21703 115 115 21..
#>  $ IMD_decile               : int [1:992818] 9 7 1 1 7 1 10 10 4 4 ..
#>  $ Income_rank              : int [1:992818] 30254 30573 67 67 3057..
#>  $ Income_decile            : int [1:992818] 10 10 1 1 10 1 10 10 3..
#>  $ Employment_rank          : int [1:992818] 30001 29614 154 154 29..
#>  $ Employment_decile        : int [1:992818] 10 10 1 1 10 1 10 10 5..
#>  $ Crime_rank               : int [1:992818] 27174 3933 2103 2103 3..
#>  $ Crime_decile             : int [1:992818] 9 2 1 1 2 1 10 10 5 1 ..
#>  $ Health_Deprivation_rank  : int [1:992818] 8264 11514 115 115 115..
#>  $ Health_Deprivation_decile: int [1:992818] 3 4 1 1 4 1 9 9 2 3 ...
#>  $ Skill_rank               : int [1:992818] 28788 27495 138 138 27..
#>  $ Skill_decile             : int [1:992818] 9 9 1 1 9 1 10 10 7 7 ..
#> NULL

But, we have information coming from the whole UK in the sales while the data on the IMD is only about England, we therefore need to filter which leaves us with this amount of rows:

#> [1] 934103

Now let’s have a look at the final table of 934’103 observations and 21 variables which will be saved as “Final_analysis_table.csv” in the data section of the project.

Unique_transaction_code	Postcode	Price	Housing_type	New_or_old	Freehold_Leasehold	Date	LSOA_code	LSOA_name	IMD_rank	IMD_decile	Income_rank	Income_decile	Employment_rank	Employment_decile	Crime_rank	Crime_decile	Health_Deprivation_rank	Health_Deprivation_decile	Skill_rank	Skill_decile
{8F1B26BD-60CA-53DB-E053-6C04A8C03649}	TS17 5FF	221950	D	Y	F	2019-04-26 00:00	E01033474	Stockton-on-Tees 023F	28901	9	30254	10	30001	10	27174	9	8264	3	28788	9
{8F1B26BD-60CB-53DB-E053-6C04A8C03649}	TS15 9ZH	246995	D	Y	F	2019-03-29 00:00	E01012235	Stockton-on-Tees 024A	21703	7	30573	10	29614	10	3933	2	11514	4	27495	9
{8F1B26BD-60CC-53DB-E053-6C04A8C03649}	TS18 2FN	244950	T	Y	F	2019-05-17 00:00	E01012266	Stockton-on-Tees 014E	115	1	67	1	154	1	2103	1	115	1	138	1
{8F1B26BD-60CD-53DB-E053-6C04A8C03649}	TS18 2FN	139950	S	Y	F	2019-05-31 00:00	E01012266	Stockton-on-Tees 014E	115	1	67	1	154	1	2103	1	115	1	138	1
{8F1B26BD-60CE-53DB-E053-6C04A8C03649}	TS15 9FD	271995	D	Y	F	2019-05-31 00:00	E01012235	Stockton-on-Tees 024A	21703	7	30573	10	29614	10	3933	2	11514	4	27495	9
{8F1B26BD-60CF-53DB-E053-6C04A8C03649}	TS18 2FD	84450	T	Y	F	2019-04-26 00:00	E01012266	Stockton-on-Tees 014E	115	1	67	1	154	1	2103	1	115	1	138	1
{8F1B26BD-60D0-53DB-E053-6C04A8C03649}	TS17 5JS	354950	D	Y	F	2019-04-29 00:00	E01033478	Stockton-on-Tees 023H	31095	10	32203	10	31564	10	31499	10	29176	9	30318	10
{8F1B26BD-60D1-53DB-E053-6C04A8C03649}	TS17 5JP	279950	D	Y	F	2019-05-31 00:00	E01033478	Stockton-on-Tees 023H	31095	10	32203	10	31564	10	31499	10	29176	9	30318	10
{8F1B26BD-60D5-53DB-E053-6C04A8C03649}	TS26 0NW	115000	F	Y	L	2019-05-03 00:00	E01033467	Hartlepool 001G	11517	4	6950	3	15783	5	14069	5	3291	2	20115	7
{8F1B26BD-60D6-53DB-E053-6C04A8C03649}	TS8 9GG	145950	T	Y	F	2019-05-31 00:00	E01032553	Middlesbrough 018H	12878	4	18082	6	11783	4	1366	1	8140	3	21543	7
{8F1B26BD-60D7-53DB-E053-6C04A8C03649}	TS17 5FF	158950	S	Y	F	2019-05-31 00:00	E01033474	Stockton-on-Tees 023F	28901	9	30254	10	30001	10	27174	9	8264	3	28788	9
{8F1B26BD-60D9-53DB-E053-6C04A8C03649}	TS18 2FL	133950	T	Y	F	2019-05-24 00:00	E01012266	Stockton-on-Tees 014E	115	1	67	1	154	1	2103	1	115	1	138	1
{8F1B26BD-60DA-53DB-E053-6C04A8C03649}	TS15 9ZF	289995	D	Y	F	2019-05-24 00:00	E01012235	Stockton-on-Tees 024A	21703	7	30573	10	29614	10	3933	2	11514	4	27495	9
{8F1B26BD-60DC-53DB-E053-6C04A8C03649}	TS17 0FU	149950	S	Y	F	2019-06-17 00:00	E01012285	Stockton-on-Tees 020D	10726	4	9716	3	7030	3	22225	7	7579	3	13507	5
{8F1B26BD-60DD-53DB-E053-6C04A8C03649}	TS17 0FU	179950	S	Y	F	2019-06-14 00:00	E01012285	Stockton-on-Tees 020D	10726	4	9716	3	7030	3	22225	7	7579	3	13507	5
{8F1B26BD-60DE-53DB-E053-6C04A8C03649}	TS15 9FL	292950	D	Y	F	2019-06-20 00:00	E01012303	Stockton-on-Tees 024G	31004	10	26189	8	27374	9	32221	10	21984	7	27587	9
{8F1B26BD-60DF-53DB-E053-6C04A8C03649}	TS5 8FD	259995	D	Y	F	2019-06-19 00:00	E01012022	Middlesbrough 015A	19123	6	18568	6	18023	6	16108	5	8849	3	21353	7
{8F1B26BD-60E0-53DB-E053-6C04A8C03649}	TS5 8DW	257950	D	Y	F	2019-06-14 00:00	E01012022	Middlesbrough 015A	19123	6	18568	6	18023	6	16108	5	8849	3	21353	7
{8F1B26BD-60E1-53DB-E053-6C04A8C03649}	TS22 5GX	449950	D	Y	F	2019-06-19 00:00	E01011959	Hartlepool 014A	22123	7	24700	8	24623	8	9817	3	17385	6	27683	9
{8F1B26BD-60E2-53DB-E053-6C04A8C03649}	TS22 5TL	599950	D	Y	F	2019-06-14 00:00	E01011959	Hartlepool 014A	22123	7	24700	8	24623	8	9817	3	17385	6	27683	9
{8F1B26BD-60E3-53DB-E053-6C04A8C03649}	TS17 5JS	409950	D	Y	F	2019-05-08 00:00	E01033478	Stockton-on-Tees 023H	31095	10	32203	10	31564	10	31499	10	29176	9	30318	10
{8F1B26BD-60E4-53DB-E053-6C04A8C03649}	TS13 4RX	51000	T	N	F	2019-06-13 00:00	E01033473	Redcar and Cleveland 013E	4211	2	2581	1	2518	1	15528	5	4401	2	3024	1
{8F1B26BD-60E5-53DB-E053-6C04A8C03649}	TS26 0FN	279995	D	Y	F	2019-06-07 00:00	E01011982	Hartlepool 014E	28897	9	30081	10	27057	9	21821	7	18171	6	31537	10
{8F1B26BD-60E7-53DB-E053-6C04A8C03649}	TS10 5DF	92000	S	N	F	2019-06-21 00:00	E01012106	Redcar and Cleveland 003C	11896	4	10067	4	7141	3	21377	7	4924	2	15561	5
{8F1B26BD-60E8-53DB-E053-6C04A8C03649}	TS8 9FT	234950	D	Y	F	2019-05-28 00:00	E01032553	Middlesbrough 018H	12878	4	18082	6	11783	4	1366	1	8140	3	21543	7
{8F1B26BD-60E9-53DB-E053-6C04A8C03649}	TS5 8EJ	182950	S	Y	F	2019-01-31 00:00	E01012022	Middlesbrough 015A	19123	6	18568	6	18023	6	16108	5	8849	3	21353	7
{8F1B26BD-60EA-53DB-E053-6C04A8C03649}	TS4 2WD	167950	D	Y	F	2019-06-21 00:00	E01012026	Middlesbrough 006A	8503	3	9049	3	8432	3	2460	1	4845	2	11219	4
{8F1B26BD-60EB-53DB-E053-6C04A8C03649}	TS8 9BF	234950	D	N	F	2019-05-24 00:00	E01012046	Middlesbrough 013A	15731	5	15494	5	9994	4	5756	2	10860	4	24304	8
{8F1B26BD-60EC-53DB-E053-6C04A8C03649}	TS7 0RS	394995	D	Y	F	2019-02-08 00:00	E01032593	Middlesbrough 020F	29410	9	29986	10	24778	8	26731	9	15641	5	30323	10
{8F1B26BD-62DE-53DB-E053-6C04A8C03649}	CW10 0DU	140000	T	N	F	2019-06-28 00:00	E01018419	Cheshire East 025A	27649	9	24574	8	27346	9	16268	5	20323	7	23019	8
{8F1B26BD-62DF-53DB-E053-6C04A8C03649}	WA5 1JJ	207000	S	N	L	2019-07-17 00:00	E01012496	Warrington 016B	24718	8	25771	8	23736	8	22861	7	15861	5	22857	7
{8F1B26BD-62E0-53DB-E053-6C04A8C03649}	CH64 4BP	230000	S	N	F	2019-06-28 00:00	E01018533	Cheshire West and Chester 006B	30812	10	28399	9	23855	8	30125	10	20310	7	30080	10
{8F1B26BD-62E1-53DB-E053-6C04A8C03649}	CW5 5QR	158000	S	N	F	2019-07-19 00:00	E01018454	Cheshire East 047B	9707	3	7947	3	10175	4	13679	5	8709	3	4350	2
{8F1B26BD-62E2-53DB-E053-6C04A8C03649}	CH66 8PA	305000	D	N	F	2019-07-05 00:00	E01018360	Cheshire West and Chester 025A	20685	7	25731	8	24798	8	18552	6	19067	6	24948	8
{8F1B26BD-62E3-53DB-E053-6C04A8C03649}	CH3 9AL	275000	S	N	F	2019-06-14 00:00	E01018371	Cheshire West and Chester 046C	22761	7	19557	6	20922	7	32144	10	24606	8	23089	8
{8F1B26BD-62E4-53DB-E053-6C04A8C03649}	ST7 3RX	139000	S	N	F	2019-07-19 00:00	E01018430	Cheshire East 033F	28965	9	25176	8	23194	8	32215	10	18407	6	21905	7
{8F1B26BD-62E5-53DB-E053-6C04A8C03649}	WA16 8DL	329000	S	N	F	2019-06-28 00:00	E01018610	Cheshire East 009C	18930	6	14790	5	13028	4	18813	6	15722	5	18422	6
{8F1B26BD-62E6-53DB-E053-6C04A8C03649}	CW8 4PE	145000	S	N	F	2019-06-28 00:00	E01018672	Cheshire West and Chester 012B	9687	3	9261	3	7570	3	14358	5	7803	3	6202	2
{8F1B26BD-62E7-53DB-E053-6C04A8C03649}	WA6 6SG	235000	D	N	F	2019-06-24 00:00	E01018690	Cheshire West and Chester 002F	31325	10	30807	10	29891	10	26778	9	28692	9	32024	10
{8F1B26BD-62E8-53DB-E053-6C04A8C03649}	CH45 6UL	220000	S	N	F	2019-06-28 00:00	E01007314	Wirral 004E	12103	4	14998	5	8607	3	11699	4	6892	3	21727	7
{8F1B26BD-62E9-53DB-E053-6C04A8C03649}	CH45 4SB	204950	S	N	F	2019-07-05 00:00	E01007316	Wirral 004F	19939	7	21771	7	16777	6	18968	6	9915	4	24675	8
{8F1B26BD-62EA-53DB-E053-6C04A8C03649}	CH66 1NZ	190000	T	N	F	2019-07-10 00:00	E01018547	Cheshire West and Chester 005B	16053	5	17164	6	9881	4	15185	5	11743	4	12621	4
{8F1B26BD-62EB-53DB-E053-6C04A8C03649}	CW9 8AQ	325000	S	N	F	2019-07-01 00:00	E01018703	Cheshire West and Chester 023F	25855	8	26100	8	18945	6	26564	9	21786	7	30221	10
{8F1B26BD-62EC-53DB-E053-6C04A8C03649}	CW11 1GJ	125000	T	N	F	2019-05-31 00:00	E01018437	Cheshire East 030B	11630	4	11180	4	8050	3	19364	6	5290	2	20428	7
{8F1B26BD-62ED-53DB-E053-6C04A8C03649}	CH65 5BH	78000	S	N	F	2019-06-28 00:00	E01018552	Cheshire West and Chester 011D	8400	3	7878	3	6792	3	20705	7	4535	2	4768	2
{8F1B26BD-62EE-53DB-E053-6C04A8C03649}	CW2 6EF	85000	T	N	F	2019-06-18 00:00	E01018445	Cheshire East 045A	3719	2	3732	2	3740	2	7320	3	3171	1	3942	2
{8F1B26BD-62EF-53DB-E053-6C04A8C03649}	SK12 2BB	187500	F	N	L	2019-06-27 00:00	E01018585	Cheshire East 001A	27192	9	24620	8	20277	7	17882	6	23299	8	27941	9
{8F1B26BD-62F0-53DB-E053-6C04A8C03649}	CH44 6QD	74500	T	N	F	2019-07-15 00:00	E01007278	Wirral 008E	273	1	763	1	555	1	1624	1	142	1	1594	1
{8F1B26BD-62F1-53DB-E053-6C04A8C03649}	CW12 4RE	430000	D	N	F	2019-06-27 00:00	E01018393	Cheshire East 022A	20700	7	29112	9	29505	9	21267	7	29124	9	27174	9
{8F1B26BD-62F2-53DB-E053-6C04A8C03649}	CH66 2NQ	293000	D	N	F	2019-07-03 00:00	E01018556	Cheshire West and Chester 013A	23445	8	21970	7	16772	6	23827	8	18388	6	18543	6
{8F1B26BD-62F3-53DB-E053-6C04A8C03649}	CW2 8PP	142000	S	N	F	2019-07-01 00:00	E01018511	Cheshire East 044B	10090	4	8933	3	8595	3	17547	6	10111	4	7623	3
{8F1B26BD-62F4-53DB-E053-6C04A8C03649}	CW2 8NN	150000	S	N	F	2019-06-26 00:00	E01018512	Cheshire East 044C	10119	4	11018	4	9795	3	11923	4	6613	3	6078	2
{8F1B26BD-62F5-53DB-E053-6C04A8C03649}	CW8 1JP	140000	S	N	F	2019-06-28 00:00	E01018710	Cheshire West and Chester 020B	6834	3	5497	2	5990	2	17065	6	6629	3	2829	1
{8F1B26BD-62F6-53DB-E053-6C04A8C03649}	SK11 8PT	150000	F	N	L	2019-06-28 00:00	E01018616	Cheshire East 017B	22695	7	23438	8	16657	6	20797	7	12536	4	31565	10
{8F1B26BD-62F7-53DB-E053-6C04A8C03649}	CH4 8BN	181000	T	N	F	2019-07-01 00:00	E01018332	Cheshire West and Chester 043A	19369	6	20352	7	14454	5	17294	6	12352	4	32096	10
{8F1B26BD-62F8-53DB-E053-6C04A8C03649}	CH44 4AG	76000	T	N	F	2019-07-05 00:00	E01007271	Wirral 010E	2379	1	3059	1	2036	1	6994	3	789	1	6371	2
{8F1B26BD-62F9-53DB-E053-6C04A8C03649}	CH64 6QF	675000	D	N	F	2019-06-28 00:00	E01018537	Cheshire West and Chester 001D	28866	9	29218	9	28400	9	13059	4	24395	8	31922	10
{8F1B26BD-62FA-53DB-E053-6C04A8C03649}	SK12 1PJ	370000	S	N	F	2019-06-17 00:00	E01018664	Cheshire East 002D	28920	9	31201	10	27050	9	27976	9	23347	8	32118	10
{8F1B26BD-62FB-53DB-E053-6C04A8C03649}	CH1 3JQ	160000	T	N	F	2019-06-11 00:00	E01018327	Cheshire West and Chester 033B	7928	3	7275	3	6343	2	11164	4	2687	1	15965	5
{8F1B26BD-62FC-53DB-E053-6C04A8C03649}	CW2 5AN	270000	D	N	F	2019-06-26 00:00	E01018494	Cheshire East 048B	27976	9	29451	9	24171	8	23204	8	24754	8	23428	8
{8F1B26BD-62FD-53DB-E053-6C04A8C03649}	WA1 3HF	183000	S	N	L	2019-07-12 00:00	E01012549	Warrington 012D	27914	9	27017	9	24749	8	22810	7	18431	6	19938	7
{8F1B26BD-64EC-53DB-E053-6C04A8C03649}	CW1 6DY	150000	S	N	F	2019-06-28 00:00	E01018501	Cheshire East 038C	15053	5	13836	5	13074	4	20945	7	11263	4	9360	3
{8F1B26BD-64ED-53DB-E053-6C04A8C03649}	WA3 4LU	435000	D	N	F	2019-06-21 00:00	E01012471	Warrington 001A	23541	8	31573	10	27872	9	17285	6	10383	4	16402	5
{8F1B26BD-64EE-53DB-E053-6C04A8C03649}	CW9 5RH	169500	S	N	F	2019-07-18 00:00	E01018717	Cheshire West and Chester 021D	13737	5	14565	5	14229	5	14030	5	12519	4	9776	3
{8F1B26BD-64EF-53DB-E053-6C04A8C03649}	CW11 1BE	280000	D	N	F	2019-07-05 00:00	E01018438	Cheshire East 030C	32165	10	30968	10	30162	10	31532	10	21386	7	29657	10
{8F1B26BD-64F0-53DB-E053-6C04A8C03649}	WA5 3LB	265000	D	N	F	2019-06-07 00:00	E01012494	Warrington 015D	28971	9	28076	9	28009	9	29793	10	20667	7	27114	9
{8F1B26BD-64F1-53DB-E053-6C04A8C03649}	CH2 3FA	249950	D	N	F	2019-07-19 00:00	E01018344	Cheshire West and Chester 036B	27769	9	25180	8	26945	9	20509	7	23219	8	27073	9
{8F1B26BD-64F2-53DB-E053-6C04A8C03649}	CW1 4AY	126000	S	N	F	2019-06-21 00:00	E01018464	Cheshire East 039B	8079	3	12672	4	16609	6	2657	1	8268	3	5123	2
{8F1B26BD-64F3-53DB-E053-6C04A8C03649}	WA8 4YR	235000	D	N	F	2019-06-12 00:00	E01012421	Halton 002D	23303	8	23620	8	20115	7	19783	7	11216	4	24055	8
{8F1B26BD-64F4-53DB-E053-6C04A8C03649}	CW11 3GZ	187500	D	N	F	2019-06-21 00:00	E01018441	Cheshire East 031B	23882	8	27976	9	25408	8	23072	8	14545	5	28557	9
{8F1B26BD-64F5-53DB-E053-6C04A8C03649}	SK12 1HY	789000	D	N	F	2019-06-14 00:00	E01018663	Cheshire East 002C	31766	10	30554	10	29948	10	21881	7	25160	8	30941	10
{8F1B26BD-64F6-53DB-E053-6C04A8C03649}	WA5 3RE	147950	T	N	F	2019-06-20 00:00	E01012494	Warrington 015D	28971	9	28076	9	28009	9	29793	10	20667	7	27114	9
{8F1B26BD-64F7-53DB-E053-6C04A8C03649}	CH66 1LP	104000	T	N	F	2019-06-21 00:00	E01018546	Cheshire West and Chester 005A	4444	2	4655	2	2710	1	13895	5	2296	1	4423	2
{8F1B26BD-64F8-53DB-E053-6C04A8C03649}	CW8 1HP	90000	T	N	F	2019-06-21 00:00	E01018709	Cheshire West and Chester 020A	12929	4	14788	5	12521	4	15842	5	7753	3	14132	5
{8F1B26BD-64F9-53DB-E053-6C04A8C03649}	CH4 9EY	295000	D	N	F	2019-07-01 00:00	E01018335	Cheshire West and Chester 046A	20543	7	25696	8	26346	9	26278	9	26404	9	25716	8
{8F1B26BD-64FA-53DB-E053-6C04A8C03649}	WA16 9QJ	180000	S	N	F	2019-07-01 00:00	E01018722	Cheshire West and Chester 017E	17312	6	25352	8	21860	7	21910	7	18157	6	23555	8
{8F1B26BD-64FC-53DB-E053-6C04A8C03649}	CW12 4QP	199950	S	N	F	2019-06-28 00:00	E01018408	Cheshire East 028B	30548	10	28430	9	24339	8	30050	10	25750	8	26100	8
{8F1B26BD-64FD-53DB-E053-6C04A8C03649}	SK11 7EF	480000	D	N	F	2019-03-27 00:00	E01018628	Cheshire East 016B	29720	10	27433	9	25199	8	23746	8	24355	8	28569	9
{8F1B26BD-64FE-53DB-E053-6C04A8C03649}	CW9 7GB	168000	S	N	F	2019-06-07 00:00	E01018719	Cheshire West and Chester 021E	14244	5	12532	4	11428	4	26572	9	7119	3	11349	4
{8F1B26BD-64FF-53DB-E053-6C04A8C03649}	WA5 3SB	310000	D	N	F	2019-05-23 00:00	E01012531	Warrington 019E	26499	9	24501	8	20606	7	32280	10	19204	6	20416	7
{8F1B26BD-6500-53DB-E053-6C04A8C03649}	CW2 6PR	360000	D	N	F	2019-07-11 00:00	E01018507	Cheshire East 046F	31944	10	31112	10	25111	8	28322	9	25376	8	31037	10
{8F1B26BD-6501-53DB-E053-6C04A8C03649}	CW6 9RN	347000	T	N	F	2019-07-05 00:00	E01018481	Cheshire East 051D	16522	6	27382	9	24995	8	23050	8	30343	10	27065	9
{8F1B26BD-6502-53DB-E053-6C04A8C03649}	WA16 8LN	420000	S	N	F	2019-06-14 00:00	E01018608	Cheshire East 010E	32707	10	32502	10	32194	10	31039	10	29692	10	32692	10
{8F1B26BD-6504-53DB-E053-6C04A8C03649}	CW7 3BF	150000	D	N	F	2019-06-21 00:00	E01018749	Cheshire West and Chester 035D	18635	6	14219	5	17066	6	23250	8	18377	6	10474	4
{8F1B26BD-6505-53DB-E053-6C04A8C03649}	CW5 7JB	265000	D	N	F	2019-06-19 00:00	E01018508	Cheshire East 048D	28331	9	31988	10	27658	9	28936	9	19274	6	27519	9
{8F1B26BD-6506-53DB-E053-6C04A8C03649}	WA2 7PP	110000	T	N	F	2019-04-26 00:00	E01012525	Warrington 011F	5292	2	7261	3	6308	2	6134	2	3955	2	6549	2
{8F1B26BD-6507-53DB-E053-6C04A8C03649}	ST7 3EX	225000	D	N	F	2019-06-28 00:00	E01018417	Cheshire East 033B	22347	7	22321	7	19988	7	18402	6	18852	6	24239	8
{8F1B26BD-6508-53DB-E053-6C04A8C03649}	CW2 6GW	235000	D	N	F	2019-07-12 00:00	E01018506	Cheshire East 046E	32586	10	31522	10	30386	10	30638	10	26681	9	30290	10
{8F1B26BD-6509-53DB-E053-6C04A8C03649}	CW11 1EP	152500	F	N	L	2019-07-15 00:00	E01018442	Cheshire East 031C	27277	9	26172	8	26492	9	16587	6	25774	8	29741	10
{8F1B26BD-650A-53DB-E053-6C04A8C03649}	WA5 3NF	221000	S	N	L	2019-06-28 00:00	E01012493	Warrington 015C	28088	9	25301	8	23539	8	30243	10	16771	6	28151	9
{8F1B26BD-650B-53DB-E053-6C04A8C03649}	CW9 8FS	222500	D	N	F	2019-07-05 00:00	E01018700	Cheshire West and Chester 023D	32794	10	31863	10	31936	10	29900	10	29438	9	31731	10
{8F1B26BD-650C-53DB-E053-6C04A8C03649}	CW1 4AA	92000	T	N	F	2019-05-10 00:00	E01018464	Cheshire East 039B	8079	3	12672	4	16609	6	2657	1	8268	3	5123	2
{8F1B26BD-4595-53DB-E053-6C04A8C03649}	N1 9BT	340000	F	N	L	2019-07-15 00:00	E01002711	Islington 021B	12915	4	12596	4	14988	5	19340	6	12997	4	28538	9
{8F1B26BD-4596-53DB-E053-6C04A8C03649}	HA8 9UY	305000	F	N	L	2019-06-07 00:00	E01000192	Barnet 018A	18475	6	15682	5	19723	7	8607	3	29094	9	25275	8
{8355F009-BD69-55C5-E053-6B04A8C0D090}	BH2 5PS	130000	O	N	L	2019-01-14 00:00	E01033285	Bournemouth 017G	11627	4	12492	4	20069	7	2624	1	10201	4	12209	4
{8355F009-BD6C-55C5-E053-6B04A8C0D090}	SP8 4HB	396000	O	N	F	2019-01-31 00:00	E01020450	North Dorset 002B	29201	9	26461	9	29108	9	30263	10	31744	10	18439	6
{8355F009-BD6D-55C5-E053-6B04A8C0D090}	SP8 4EQ	197500	D	N	F	2019-01-11 00:00	E01020447	North Dorset 001B	17341	6	14400	5	16603	6	28663	9	16652	6	6405	2
{8355F009-BD6E-55C5-E053-6B04A8C0D090}	BH4 9JY	230000	F	N	L	2019-01-28 00:00	E01033286	Bournemouth 023C	20471	7	18636	6	23196	8	9966	4	19477	6	23657	8
{8355F009-BD6F-55C5-E053-6B04A8C0D090}	BH12 1AW	215500	F	N	L	2019-01-17 00:00	E01015386	Poole 009A	9710	3	8440	3	11402	4	9071	3	14073	5	9960	4
{8355F009-BD70-55C5-E053-6B04A8C0D090}	DT11 7FS	242000	O	N	F	2019-02-08 00:00	E01020436	North Dorset 007B	21670	7	19476	6	22455	7	28330	9	29399	9	13968	5
{8355F009-BD71-55C5-E053-6B04A8C0D090}	BH16 6EH	900000	D	N	F	2019-01-22 00:00	E01020470	Purbeck 001C	32050	10	28118	9	30187	10	27918	9	27412	9	29132	9
{8355F009-BD72-55C5-E053-6B04A8C0D090}	SP8 5PX	427000	O	N	F	2019-02-01 00:00	E01020450	North Dorset 002B	29201	9	26461	9	29108	9	30263	10	31744	10	18439	6
{8355F009-BD75-55C5-E053-6B04A8C0D090}	BH2 6BY	262000	F	N	L	2019-01-16 00:00	E01033286	Bournemouth 023C	20471	7	18636	6	23196	8	9966	4	19477	6	23657	8
{8355F009-BD76-55C5-E053-6B04A8C0D090}	BH1 1LD	150000	O	N	L	2019-02-11 00:00	E01015285	Bournemouth 021A	12504	4	16352	5	16440	6	2575	1	12327	4	24052	8
{8355F009-BD77-55C5-E053-6B04A8C0D090}	DT7 3DB	149500	F	N	L	2019-02-04 00:00	E01020532	West Dorset 005B	28011	9	20444	7	28360	9	24050	8	27884	9	27934	9
{8355F009-BD7B-55C5-E053-6B04A8C0D090}	SP7 0QW	350000	O	N	F	2019-02-15 00:00	E01020462	North Dorset 002D	15688	5	22914	7	24266	8	29905	10	26957	9	20077	7
{8355F009-BD7D-55C5-E053-6B04A8C0D090}	DT6 4BP	668375	D	N	F	2019-01-25 00:00	E01020504	West Dorset 008C	24687	8	25394	8	22571	7	29370	9	25545	8	21969	7
{8355F009-BD99-55C5-E053-6B04A8C0D090}	BH10 5JG	285000	D	N	F	2019-01-31 00:00	E01015305	Bournemouth 001C	6513	2	5926	2	6651	3	11921	4	6775	3	4125	2
{8355F009-BD9A-55C5-E053-6B04A8C0D090}	DT9 6HY	455000	O	N	F	2019-01-25 00:00	E01020508	West Dorset 002B	18750	6	27025	9	29294	9	32489	10	29843	10	22885	7
{8355F009-BD9B-55C5-E053-6B04A8C0D090}	DT5 2NQ	80000	O	N	F	2019-02-06 00:00	E01020566	Weymouth and Portland 009D	18877	6	21250	7	17951	6	28058	9	14590	5	13172	5
{8355F009-BD9C-55C5-E053-6B04A8C0D090}	DT2 8GA	200000	O	Y	F	2019-01-31 00:00	E01020537	West Dorset 011B	20194	7	24056	8	22800	7	22341	7	26658	9	19306	6
{8355F009-BD9E-55C5-E053-6B04A8C0D090}	BH10 4EB	265000	D	N	F	2019-01-31 00:00	E01015337	Bournemouth 003E	19516	6	17025	6	17353	6	22193	7	12373	4	17550	6
{8355F009-BDA0-55C5-E053-6B04A8C0D090}	BH22 9DP	395000	O	N	F	2019-02-08 00:00	E01020399	East Dorset 011B	27760	9	24594	8	23127	8	26396	9	29491	9	20274	7
{8355F009-BDA1-55C5-E053-6B04A8C0D090}	BH1 4EX	78000	F	N	L	2019-02-21 00:00	E01015282	Bournemouth 019E	528	1	1747	1	511	1	902	1	610	1	4798	2
{8355F009-BDA3-55C5-E053-6B04A8C0D090}	BH14 9AH	449000	D	N	F	2019-02-08 00:00	E01015462	Poole 013D	19863	7	18021	6	16270	5	17852	6	18757	6	26927	9
{8355F009-BDA5-55C5-E053-6B04A8C0D090}	BH8 0AG	340000	O	N	F	2019-02-08 00:00	E01015352	Bournemouth 004D	21029	7	17923	6	20880	7	29057	9	20406	7	14595	5
{8355F009-BDA6-55C5-E053-6B04A8C0D090}	BH17 9DU	245000	T	N	F	2019-02-15 00:00	E01015415	Poole 004D	6851	3	5823	2	6459	2	20408	7	4879	2	3047	1
{8355F009-BDA7-55C5-E053-6B04A8C0D090}	BH9 1HR	260000	O	N	F	2019-02-11 00:00	E01015373	Bournemouth 010D	18427	6	18130	6	16934	6	16166	5	13595	5	22284	7
{8355F009-BDA8-55C5-E053-6B04A8C0D090}	DT4 8DN	350000	O	N	F	2019-02-15 00:00	E01020554	Weymouth and Portland 004B	1142	1	4292	2	1687	1	303	1	398	1	4008	2
{8355F009-BDA9-55C5-E053-6B04A8C0D090}	BH15 4JY	115000	O	N	F	2019-02-14 00:00	E01015427	Poole 014A	15147	5	17227	6	15524	5	23087	8	12344	4	10644	4
{8355F009-BDAA-55C5-E053-6B04A8C0D090}	BH21 6SX	485000	O	N	F	2019-01-31 00:00	E01020412	East Dorset 003B	13434	5	12062	4	15189	5	14255	5	26259	8	4911	2
{8355F009-BDAD-55C5-E053-6B04A8C0D090}	SR7 7RQ	55000	T	N	F	2019-01-25 00:00	E01020742	County Durham 017C	6644	3	5544	2	3806	2	12676	4	3824	2	8144	3
{8355F009-BDAE-55C5-E053-6B04A8C0D090}	DH1 1ST	2280000	O	N	F	2019-02-15 00:00	E01020690	County Durham 028C	21974	7	20486	7	17865	6	21414	7	9784	3	23670	8
{8355F009-BDAF-55C5-E053-6B04A8C0D090}	SR8 4LX	23000	T	N	F	2019-01-17 00:00	E01020764	County Durham 036A	291	1	748	1	77	1	29	1	527	1	915	1
{8355F009-BDB0-55C5-E053-6B04A8C0D090}	SR8 4BH	44000	T	N	F	2019-02-08 00:00	E01020764	County Durham 036A	291	1	748	1	77	1	29	1	527	1	915	1
{8355F009-BDB2-55C5-E053-6B04A8C0D090}	SR8 4BZ	28000	T	N	F	2019-01-31 00:00	E01020767	County Durham 036C	569	1	1552	1	207	1	56	1	155	1	3016	1
{8355F009-B361-55C5-E053-6B04A8C0D090}	WF9 2FR	125000	D	N	F	2019-01-25 00:00	E01011862	Wakefield 044C	4599	2	6018	2	4289	2	3095	1	2352	1	4848	2
{8355F009-B362-55C5-E053-6B04A8C0D090}	WF2 0DU	130000	T	N	F	2019-02-08 00:00	E01011924	Wakefield 019C	12988	4	15330	5	16328	5	6176	2	11892	4	9673	3
{8355F009-B364-55C5-E053-6B04A8C0D090}	LS8 3AP	159000	S	N	F	2019-02-08 00:00	E01011424	Leeds 047B	4665	2	6380	2	7812	3	672	1	10778	4	3190	1
{8355F009-B366-55C5-E053-6B04A8C0D090}	LS19 6QA	240000	T	N	F	2019-01-18 00:00	E01011457	Leeds 027C	28797	9	30576	10	31781	10	25620	8	20632	7	31836	10
{8355F009-B367-55C5-E053-6B04A8C0D090}	BD9 4LS	65000	S	N	F	2019-02-08 00:00	E01010793	Bradford 025D	6952	3	9378	3	10305	4	2821	1	10677	4	10693	4
{8355F009-B369-55C5-E053-6B04A8C0D090}	HD4 5SS	109000	T	N	L	2019-01-31 00:00	E01011154	Kirklees 045D	9774	3	7205	3	12093	4	8190	3	11745	4	5816	2
{8355F009-B36A-55C5-E053-6B04A8C0D090}	BD12 0JT	142000	S	N	F	2019-01-17 00:00	E01010865	Bradford 060D	11215	4	17515	6	15988	5	3657	2	11571	4	8499	3
{8355F009-B36D-55C5-E053-6B04A8C0D090}	BD18 2BW	138000	S	N	F	2019-02-08 00:00	E01010779	Bradford 021C	4351	2	5552	2	4775	2	617	1	4912	2	4421	2
{8355F009-B36E-55C5-E053-6B04A8C0D090}	BD22 8JL	161250	T	N	F	2019-02-01 00:00	E01010854	Bradford 023A	12588	4	16525	6	12904	4	8196	3	10244	4	15048	5
{8355F009-B370-55C5-E053-6B04A8C0D090}	WF4 5DE	104000	T	N	F	2019-02-08 00:00	E01011802	Wakefield 031D	17370	6	15920	5	16245	5	11040	4	14747	5	17545	6
{8355F009-B371-55C5-E053-6B04A8C0D090}	BD10 0AT	109000	T	N	F	2019-02-04 00:00	E01010654	Bradford 027C	1052	1	1737	1	1940	1	19	1	3332	2	598	1
{8355F009-B375-55C5-E053-6B04A8C0D090}	WF1 2FJ	270000	D	N	F	2019-02-15 00:00	E01011887	Wakefield 008B	26407	9	29115	9	27929	9	15250	5	19308	6	21217	7
{8355F009-B377-55C5-E053-6B04A8C0D090}	WF2 8JL	193000	S	N	F	2019-01-07 00:00	E01011903	Wakefield 028B	8408	3	13086	4	5029	2	4211	2	4734	2	11297	4
{8355F009-B37B-55C5-E053-6B04A8C0D090}	HD7 5HN	535000	D	N	F	2019-01-31 00:00	E01011073	Kirklees 049C	10245	4	10698	4	10042	4	13037	4	9074	3	12997	4
{8355F009-B37D-55C5-E053-6B04A8C0D090}	LS17 5BE	140000	F	N	L	2019-02-07 00:00	E01011514	Leeds 025E	23267	8	26571	9	22732	7	12059	4	19655	6	28897	9
{8355F009-B37F-55C5-E053-6B04A8C0D090}	HX7 8DZ	220000	F	N	L	2019-01-25 00:00	E01010888	Calderdale 004E	14403	5	14517	5	14232	5	15357	5	11848	4	28137	9
{8355F009-B380-55C5-E053-6B04A8C0D090}	WF8 2QS	152500	S	N	F	2019-01-31 00:00	E01011853	Wakefield 018D	6102	2	6026	2	4905	2	11764	4	5779	2	2608	1
{8355F009-B382-55C5-E053-6B04A8C0D090}	LS4 2SE	45000	F	N	L	2019-01-31 00:00	E01011480	Leeds 045B	16197	5	24348	8	20838	7	2286	1	14533	5	20462	7
{8355F009-B386-55C5-E053-6B04A8C0D090}	WF14 9FA	208000	S	N	F	2019-01-14 00:00	E01011216	Kirklees 021A	24655	8	24086	8	25731	8	9270	3	16691	6	27945	9
{8355F009-B387-55C5-E053-6B04A8C0D090}	WF5 9EH	187500	S	N	F	2019-01-11 00:00	E01011828	Wakefield 021F	19711	7	20260	7	23464	8	10659	4	17072	6	13180	5
{8355F009-B388-55C5-E053-6B04A8C0D090}	LS19 7HG	162000	T	N	F	2019-02-01 00:00	E01011273	Leeds 010B	19375	6	19671	6	19396	6	13259	5	12938	4	22866	7
{8355F009-B389-55C5-E053-6B04A8C0D090}	HD3 3FW	123000	T	N	F	2019-01-25 00:00	E01011070	Kirklees 052A	18464	6	20281	7	21895	7	18121	6	25480	8	23408	8
{8355F009-B38D-55C5-E053-6B04A8C0D090}	WF6 1EP	98500	T	N	F	2019-02-18 00:00	E01011822	Wakefield 016F	8959	3	12970	4	12406	4	1176	1	6558	2	6094	2
{8355F009-B38E-55C5-E053-6B04A8C0D090}	LS13 1GH	195000	T	N	F	2019-01-18 00:00	E01011325	Leeds 046B	7939	3	10261	4	8559	3	2372	1	7083	3	8708	3
{8355F009-B390-55C5-E053-6B04A8C0D090}	BD6 2AR	137000	S	N	F	2019-01-14 00:00	E01010867	Bradford 059G	8448	3	6875	3	9708	3	3745	2	8953	3	5796	2
{8355F009-B391-55C5-E053-6B04A8C0D090}	HD9 2AA	510000	D	N	F	2019-01-10 00:00	E01011180	Kirklees 058A	27915	9	27554	9	27065	9	25146	8	26524	9	28859	9
{8355F009-B395-55C5-E053-6B04A8C0D090}	BD22 7FA	168000	D	N	F	2019-02-15 00:00	E01010862	Bradford 014C	23732	8	21529	7	22751	7	22542	7	14862	5	20650	7
{8355F009-B396-55C5-E053-6B04A8C0D090}	WF1 3PR	64000	F	N	L	2019-02-01 00:00	E01011912	Wakefield 017B	3384	2	5426	2	2354	1	2308	1	5052	2	3093	1
{8355F009-B71B-55C5-E053-6B04A8C0D090}	BS6 7SS	450000	T	N	F	2019-02-06 00:00	E01014620	Bristol 011D	30412	10	30612	10	25055	8	14399	5	28682	9	32271	10
{8355F009-B71C-55C5-E053-6B04A8C0D090}	BS3 1HT	210000	T	N	F	2019-01-29 00:00	E01033361	Bristol 039F	4598	2	6998	3	8546	3	67	1	1348	1	17469	6
{8355F009-B71D-55C5-E053-6B04A8C0D090}	BS16 1QB	225000	F	N	L	2019-01-25 00:00	E01014660	Bristol 014A	4499	2	5337	2	5603	2	4469	2	4797	2	2355	1
{8355F009-B722-55C5-E053-6B04A8C0D090}	BS3 2BX	450000	O	N	F	2019-01-31 00:00	E01014700	Bristol 036E	25217	8	30726	10	27006	9	9798	3	20989	7	20290	7
{8355F009-B724-55C5-E053-6B04A8C0D090}	BS3 5DP	175000	F	N	L	2019-01-15 00:00	E01014579	Bristol 045A	6107	2	6939	3	7118	3	5296	2	6873	3	4344	2
{8355F009-B725-55C5-E053-6B04A8C0D090}	BS3 5DP	195000	F	N	L	2019-01-14 00:00	E01014579	Bristol 045A	6107	2	6939	3	7118	3	5296	2	6873	3	4344	2
{8355F009-B730-55C5-E053-6B04A8C0D090}	BS1 6FL	488334	O	N	L	2019-02-05 00:00	E01033355	Bristol 054C	8878	3	11556	4	11748	4	12190	4	9347	3	9787	3
{8355F009-B731-55C5-E053-6B04A8C0D090}	BS7 0JP	280000	T	N	L	2019-02-08 00:00	E01014634	Bristol 005B	23040	8	25858	8	30224	10	6434	2	17408	6	24755	8
{8355F009-B735-55C5-E053-6B04A8C0D090}	BS5 7SP	229000	T	N	F	2019-01-23 00:00	E01014626	Bristol 021C	6515	2	6726	3	7207	3	5626	2	6937	3	8111	3
{8355F009-B737-55C5-E053-6B04A8C0D090}	BS6 6SU	825000	T	N	F	2019-01-11 00:00	E01014559	Bristol 022C	26995	9	27939	9	31104	10	18496	6	20839	7	31117	10
{8355F009-B73A-55C5-E053-6B04A8C0D090}	BS8 4RJ	975000	O	N	F	2019-02-06 00:00	E01014549	Bristol 034B	15519	5	15656	5	15643	5	15152	5	18901	6	28271	9
{8355F009-B73B-55C5-E053-6B04A8C0D090}	BS1 5JG	950000	O	N	F	2019-02-21 00:00	E01014542	Bristol 032C	18266	6	29666	10	32266	10	6443	2	10281	4	31234	10
{8355F009-B73C-55C5-E053-6B04A8C0D090}	BS7 8JJ	820	O	N	F	2019-02-11 00:00	E01014666	Bristol 017C	30477	10	30416	10	30609	10	15338	5	30143	10	32204	10
{8355F009-B73D-55C5-E053-6B04A8C0D090}	BS7 8JJ	820	O	N	F	2019-01-11 00:00	E01014666	Bristol 017C	30477	10	30416	10	30609	10	15338	5	30143	10	32204	10
{8355F009-B73E-55C5-E053-6B04A8C0D090}	BS7 8JJ	820	O	N	F	2019-02-11 00:00	E01014666	Bristol 017C	30477	10	30416	10	30609	10	15338	5	30143	10	32204	10
{8355F009-B73F-55C5-E053-6B04A8C0D090}	BS3 5AU	290000	O	N	F	2019-01-09 00:00	E01014736	Bristol 040D	9837	3	11490	4	12021	4	7610	3	7188	3	6364	2
{8355F009-B741-55C5-E053-6B04A8C0D090}	BS2 8HD	410000	O	N	F	2019-01-21 00:00	E01014542	Bristol 032C	18266	6	29666	10	32266	10	6443	2	10281	4	31234	10
{8355F009-B742-55C5-E053-6B04A8C0D090}	BS6 6JA	465000	O	N	F	2019-01-30 00:00	E01014560	Bristol 022D	25109	8	28102	9	29421	9	13123	4	20345	7	32148	10
{8355F009-B743-55C5-E053-6B04A8C0D090}	BS13 8LU	245000	T	N	F	2019-01-21 00:00	E01014515	Bristol 050A	4064	2	5842	2	5675	2	1744	1	5305	2	1203	1
{8355F009-B744-55C5-E053-6B04A8C0D090}	BS14 9EA	380000	S	N	F	2019-02-04 00:00	E01014708	Bristol 049G	15316	5	18647	6	16812	6	5709	2	15395	5	10884	4
{8355F009-B745-55C5-E053-6B04A8C0D090}	BS14 9AL	115000	F	N	L	2019-02-13 00:00	E01014613	Bristol 047E	15211	5	17190	6	16563	6	11370	4	13886	5	8890	3
{8355F009-B746-55C5-E053-6B04A8C0D090}	BS1 1RU	40500	O	N	F	2019-01-16 00:00	E01014540	Bristol 032B	12154	4	21851	7	26159	8	1511	1	16466	6	12672	4
{8355F009-B747-55C5-E053-6B04A8C0D090}	BS14 0AH	220000	S	N	F	2019-01-28 00:00	E01014607	Bristol 047A	11390	4	15461	5	17841	6	613	1	12192	4	8193	3
{8355F009-B748-55C5-E053-6B04A8C0D090}	BS7 9ES	343000	O	N	L	2019-01-22 00:00	E01014508	Bristol 016B	18629	6	24377	8	22507	7	5325	2	13908	5	30400	10
{8355F009-B749-55C5-E053-6B04A8C0D090}	BS4 3LT	260000	T	N	F	2019-01-31 00:00	E01014531	Bristol 035D	18045	6	20893	7	25550	8	10736	4	19931	7	17333	6
{8355F009-B74A-55C5-E053-6B04A8C0D090}	BS3 4EY	650000	O	N	L	2019-02-15 00:00	E01033361	Bristol 039F	4598	2	6998	3	8546	3	67	1	1348	1	17469	6
{8355F009-B74B-55C5-E053-6B04A8C0D090}	BS7 0UL	332500	S	N	F	2019-01-25 00:00	E01014631	Bristol 004A	16300	5	13649	5	13598	5	17356	6	6589	3	24644	8
{8355F009-B74C-55C5-E053-6B04A8C0D090}	BS8 1LP	1007500	S	N	F	2019-01-21 00:00	E01014551	Bristol 026A	20720	7	29405	9	31404	10	10766	4	15353	5	21289	7
{8355F009-B74D-55C5-E053-6B04A8C0D090}	BS1 1NR	341763	O	N	L	2019-01-25 00:00	E01014540	Bristol 032B	12154	4	21851	7	26159	8	1511	1	16466	6	12672	4
{8355F009-B74E-55C5-E053-6B04A8C0D090}	MK2 2HN	322500	D	N	F	2019-01-23 00:00	E01016710	Milton Keynes 030A	10999	4	10903	4	12267	4	3525	2	13902	5	7549	3
{8355F009-BA17-55C5-E053-6B04A8C0D090}	TR16 5TP	101000	T	N	F	2019-01-16 00:00	E01018916	Cornwall 050A	9892	4	10608	4	10340	4	23781	8	11711	4	10435	4
{8355F009-BA1B-55C5-E053-6B04A8C0D090}	TR27 5AF	127500	O	N	F	2019-01-31 00:00	E01018982	Cornwall 057C	11436	4	10212	4	12156	4	19848	7	19434	6	8126	3
{8355F009-BA1C-55C5-E053-6B04A8C0D090}	TR18 2HZ	140000	O	N	F	2019-01-28 00:00	E01018999	Cornwall 068C	3874	2	3910	2	3100	1	3950	2	4366	2	14325	5
{8355F009-BA1D-55C5-E053-6B04A8C0D090}	TR7 2TB	332500	D	N	F	2019-01-21 00:00	E01019018	Cornwall 021A	23996	8	22051	7	19403	6	30336	10	19803	7	25336	8
{8355F009-BA20-55C5-E053-6B04A8C0D090}	TR4 9LF	208332	O	N	F	2019-01-22 00:00	E01018819	Cornwall 043A	20905	7	18065	6	15733	5	30311	10	19882	7	15408	5
{8355F009-BA21-55C5-E053-6B04A8C0D090}	TR27 4DY	120000	F	N	L	2019-02-05 00:00	E01018982	Cornwall 057C	11436	4	10212	4	12156	4	19848	7	19434	6	8126	3
{8355F009-BA22-55C5-E053-6B04A8C0D090}	EX23 0EH	222222	O	N	F	2019-01-18 00:00	E01018951	Cornwall 002B	10912	4	16402	5	16818	6	30514	10	25948	8	13305	5
{8355F009-BA23-55C5-E053-6B04A8C0D090}	TR26 3HW	136000	O	N	F	2019-01-31 00:00	E01018985	Cornwall 058A	19312	6	19990	7	16782	6	31963	10	27628	9	20868	7
{8355F009-BA24-55C5-E053-6B04A8C0D090}	PL25 4AN	35000	O	N	F	2019-01-24 00:00	E01019047	Cornwall 038D	7549	3	9415	3	3632	2	8490	3	7380	3	14247	5
{8355F009-BA27-55C5-E053-6B04A8C0D090}	EX23 0EH	265000	O	N	F	2019-01-17 00:00	E01018951	Cornwall 002B	10912	4	16402	5	16818	6	30514	10	25948	8	13305	5
{8355F009-BA29-55C5-E053-6B04A8C0D090}	PL26 7AW	375000	O	N	F	2019-02-15 00:00	E01019067	Cornwall 041E	14793	5	19553	6	23145	8	28765	9	20079	7	24123	8
{8355F009-BA2A-55C5-E053-6B04A8C0D090}	TR19 6JB	500000	O	N	F	2019-01-14 00:00	E01018992	Cornwall 069A	14154	5	16459	6	17451	6	25368	8	21735	7	25718	8
{8355F009-BA2B-55C5-E053-6B04A8C0D090}	PL31 2HU	315000	O	N	F	2019-01-18 00:00	E01018933	Cornwall 014B	2579	1	2914	1	2402	1	5118	2	2548	1	4027	2
{8355F009-BA2D-55C5-E053-6B04A8C0D090}	PL26 6AZ	1220000	O	N	F	2019-01-24 00:00	E01019067	Cornwall 041E	14793	5	19553	6	23145	8	28765	9	20079	7	24123	8
{8355F009-BA30-55C5-E053-6B04A8C0D090}	TR9 6NE	218000	S	N	F	2019-02-01 00:00	E01019065	Cornwall 019F	13499	5	14322	5	13553	5	32117	10	13125	4	6446	2
{8355F009-BA31-55C5-E053-6B04A8C0D090}	PL14 4NP	152000	O	N	L	2019-01-28 00:00	E01018758	Cornwall 016A	10481	4	12918	4	9861	4	26475	9	12038	4	8075	3
{8355F009-BA33-55C5-E053-6B04A8C0D090}	TR7 1NJ	525000	O	N	F	2019-01-29 00:00	E01019028	Cornwall 020A	8820	3	7407	3	6990	3	10375	4	9599	3	18868	6
{8355F009-BA34-55C5-E053-6B04A8C0D090}	TR7 1NA	295000	T	N	F	2019-02-01 00:00	E01019028	Cornwall 020A	8820	3	7407	3	6990	3	10375	4	9599	3	18868	6
{8355F009-BA35-55C5-E053-6B04A8C0D090}	PL26 8EP	146000	O	N	F	2019-01-25 00:00	E01019052	Cornwall 024A	8372	3	11419	4	11051	4	27662	9	13885	5	4123	2
{8355F009-BA36-55C5-E053-6B04A8C0D090}	PL12 5BJ	126770	F	N	L	2019-01-25 00:00	E01018785	Cornwall 023D	13965	5	19370	6	19601	6	27346	9	22152	7	19921	7
{8355F009-BA37-55C5-E053-6B04A8C0D090}	EX23 0DJ	39995	O	N	L	2019-02-08 00:00	E01018951	Cornwall 002B	10912	4	16402	5	16818	6	30514	10	25948	8	13305	5
{8355F009-BA39-55C5-E053-6B04A8C0D090}	TR8 5RL	975000	D	N	F	2019-01-18 00:00	E01019031	Cornwall 020D	13161	5	15433	5	14997	5	21007	7	15632	5	18348	6
{8355F009-BA3A-55C5-E053-6B04A8C0D090}	TR2 4PZ	275000	S	N	F	2019-02-01 00:00	E01019066	Cornwall 041D	14986	5	16298	5	23697	8	32141	10	20500	7	24220	8
{8355F009-BA3D-55C5-E053-6B04A8C0D090}	EX23 8FJ	415000	D	N	F	2019-01-25 00:00	E01018937	Cornwall 001B	8452	3	5833	2	4231	2	26938	9	15372	5	5817	2
{8355F009-BA3E-55C5-E053-6B04A8C0D090}	TR7 2NH	265000	T	N	F	2019-01-25 00:00	E01019020	Cornwall 021C	3218	1	3593	2	1907	1	7177	3	2829	1	8769	3
{8355F009-BA3F-55C5-E053-6B04A8C0D090}	TR27 4QT	168000	D	N	F	2019-02-07 00:00	E01018983	Cornwall 057D	22261	7	19133	6	18333	6	24886	8	18353	6	23509	8
{8355F009-BA40-55C5-E053-6B04A8C0D090}	PL17 7DF	215000	O	N	F	2019-02-18 00:00	E01018752	Cornwall 013C	17741	6	17682	6	15630	5	26524	9	17091	6	14635	5
{8355F009-BA44-55C5-E053-6B04A8C0D090}	PL30 3JZ	550000	O	N	F	2019-01-31 00:00	E01018940	Cornwall 003A	14805	5	15531	5	15664	5	30958	10	16900	6	20303	7
{8355F009-BA4A-55C5-E053-6B04A8C0D090}	PL11 2AW	12000	O	N	L	2019-01-11 00:00	E01018797	Cornwall 029A	5989	2	5298	2	4216	2	15493	5	2413	1	8906	3
{8355F009-BDB4-55C5-E053-6B04A8C0D090}	DL16 6HP	30000	T	N	F	2019-02-12 00:00	E01020842	County Durham 049D	6159	2	4423	2	3676	2	16229	5	6834	3	4150	2
{8355F009-BDB5-55C5-E053-6B04A8C0D090}	DL15 0PD	15000	O	N	F	2019-02-11 00:00	E01020904	County Durham 046F	11291	4	11700	4	7251	3	3544	2	5781	2	20081	7
{8355F009-BDB6-55C5-E053-6B04A8C0D090}	SR8 3DQ	51000	T	N	F	2019-02-04 00:00	E01020751	County Durham 025A	6088	2	8518	3	2889	1	4439	2	3390	2	6824	3
{8355F009-BDB7-55C5-E053-6B04A8C0D090}	DL15 8PY	39999	T	N	F	2019-01-25 00:00	E01020898	County Durham 045F	906	1	600	1	271	1	12657	4	632	1	3099	1
{8355F009-BDB8-55C5-E053-6B04A8C0D090}	DH9 7AW	30000	O	N	F	2019-01-18 00:00	E01020671	County Durham 009D	1680	1	1675	1	711	1	1905	1	2524	1	3087	1
{8355F009-BDB9-55C5-E053-6B04A8C0D090}	SR7 8JW	70000	S	N	F	2019-02-06 00:00	E01020787	County Durham 016E	8076	3	5781	2	3965	2	13595	5	7221	3	8797	3
{8355F009-BDBA-55C5-E053-6B04A8C0D090}	DL14 7DG	32000	T	N	F	2019-01-18 00:00	E01020872	County Durham 056C	11087	4	10352	4	8918	3	5510	2	5141	2	16544	6
{8355F009-BDBB-55C5-E053-6B04A8C0D090}	DL2 2TU	575000	O	N	F	2019-02-01 00:00	E01012334	Darlington 001B	18804	6	26934	9	25451	8	15696	5	19524	6	28396	9
{8355F009-BDBF-55C5-E053-6B04A8C0D090}	DH9 9RT	190000	D	N	F	2019-01-17 00:00	E01020676	County Durham 001E	16102	5	14831	5	10815	4	28088	9	7027	3	16397	5
{8355F009-BDC0-55C5-E053-6B04A8C0D090}	SR8 3LZ	32750	T	N	F	2019-02-04 00:00	E01020751	County Durham 025A	6088	2	8518	3	2889	1	4439	2	3390	2	6824	3
{8355F009-BDC1-55C5-E053-6B04A8C0D090}	DL1 4DT	72000	T	N	F	2019-02-01 00:00	E01012304	Darlington 012A	303	1	357	1	374	1	766	1	340	1	1088	1
{8355F009-BDC2-55C5-E053-6B04A8C0D090}	DH6 1NG	28000	T	N	F	2019-02-06 00:00	E01020729	County Durham 027D	7365	3	6889	3	5856	2	7074	3	8509	3	8149	3
{8355F009-BDC3-55C5-E053-6B04A8C0D090}	DH9 9PJ	45500	T	N	F	2019-01-21 00:00	E01020676	County Durham 001E	16102	5	14831	5	10815	4	28088	9	7027	3	16397	5
{8355F009-BDC5-55C5-E053-6B04A8C0D090}	DL14 7DL	37000	T	N	F	2019-01-18 00:00	E01020869	County Durham 055B	5895	2	6458	2	4558	2	2551	1	3876	2	11822	4
{8355F009-BDC6-55C5-E053-6B04A8C0D090}	SR7 7UB	150000	O	N	F	2019-02-01 00:00	E01020740	County Durham 017A	14665	5	14158	5	11034	4	12563	4	7333	3	11461	4
{8355F009-BDC8-55C5-E053-6B04A8C0D090}	DL3 0NX	73000	T	N	F	2019-01-11 00:00	E01012349	Darlington 004A	552	1	662	1	643	1	552	1	498	1	1383	1
{8355F009-BDC9-55C5-E053-6B04A8C0D090}	DL5 7QD	175000	D	N	F	2019-02-15 00:00	E01020814	County Durham 060B	15674	5	14750	5	14178	5	11275	4	6367	2	20356	7
{8355F009-BDCA-55C5-E053-6B04A8C0D090}	DL3 0GZ	105000	T	N	F	2019-01-25 00:00	E01012309	Darlington 006A	24336	8	26043	8	21114	7	5952	2	19410	6	23084	8
{8355F009-BDCB-55C5-E053-6B04A8C0D090}	SR4 6LZ	45000	T	N	F	2019-02-19 00:00	E01008757	Sunderland 015A	5051	2	4454	2	3829	2	2127	1	2676	1	11172	4
{8355F009-BDCF-55C5-E053-6B04A8C0D090}	DH3 3NE	115000	T	N	F	2019-01-25 00:00	E01020595	County Durham 013B	24802	8	25526	8	18190	6	13955	5	12879	4	29998	10
{8355F009-BDD0-55C5-E053-6B04A8C0D090}	DL14 9SS	170000	O	N	F	2019-02-06 00:00	E01020907	County Durham 058C	3254	1	2835	1	2167	1	3061	1	4436	2	2558	1
{8355F009-BDD1-55C5-E053-6B04A8C0D090}	SR8 4EH	32500	T	N	F	2019-01-28 00:00	E01020767	County Durham 036C	569	1	1552	1	207	1	56	1	155	1	3016	1
{8355F009-BDD2-55C5-E053-6B04A8C0D090}	DL13 4BD	55000	T	N	F	2019-02-14 00:00	E01020892	County Durham 045D	6236	2	5362	2	4016	2	6095	2	5629	2	8612	3
{8355F009-BDD3-55C5-E053-6B04A8C0D090}	DL17 8BP	90000	D	N	F	2019-01-18 00:00	E01033203	County Durham 053E	5925	2	5137	2	3604	2	4378	2	7174	3	6463	2
{8355F009-BDD4-55C5-E053-6B04A8C0D090}	SR8 3PX	17000	T	N	F	2019-01-17 00:00	E01020752	County Durham 025B	221	1	376	1	33	1	2	1	536	1	1330	1
{8355F009-BDD5-55C5-E053-6B04A8C0D090}	DL15 0EW	50000	T	N	F	2019-01-31 00:00	E01020903	County Durham 046E	11996	4	11856	4	9801	3	8459	3	6820	3	20707	7
{8355F009-BDD7-55C5-E053-6B04A8C0D090}	DL14 8UZ	20000	T	N	F	2019-02-14 00:00	E01020838	County Durham 059C	4453	2	4730	2	3656	2	1052	1	3864	2	7645	3
{8355F009-BDD8-55C5-E053-6B04A8C0D090}	DH8 5FE	98500	T	N	L	2019-02-05 00:00	E01020644	County Durham 014D	10998	4	8960	3	8708	3	12584	4	6863	3	9783	3
{8355F009-BDD9-55C5-E053-6B04A8C0D090}	DH7 0TP	600000	O	N	F	2019-02-01 00:00	E01020664	County Durham 020B	28226	9	27355	9	30613	10	20919	7	19557	6	30070	10
{8355F009-BDDA-55C5-E053-6B04A8C0D090}	DH8 5FD	98500	T	N	L	2019-02-05 00:00	E01020644	County Durham 014D	10998	4	8960	3	8708	3	12584	4	6863	3	9783	3
{8355F009-BDDB-55C5-E053-6B04A8C0D090}	DH9 6BA	43000	T	N	F	2019-02-01 00:00	E01020649	County Durham 008C	7293	3	5876	2	4128	2	11448	4	7242	3	6147	2
{8355F009-BDDD-55C5-E053-6B04A8C0D090}	DL1 5AQ	15000	O	N	L	2019-01-23 00:00	E01012357	Darlington 014B	5090	2	5646	2	6549	2	2172	1	4689	2	3865	2
{8355F009-BDDE-55C5-E053-6B04A8C0D090}	DL1 4RY	100000	T	N	F	2019-01-31 00:00	E01012318	Darlington 013B	2843	1	2761	1	2616	1	1670	1	3014	1	2063	1
{8355F009-B397-55C5-E053-6B04A8C0D090}	LS6 3QF	439750	S	N	F	2019-02-18 00:00	E01011694	Leeds 109F	25853	8	26673	9	31020	10	11703	4	24783	8	29634	10
{8355F009-B39A-55C5-E053-6B04A8C0D090}	HX2 0SR	208500	S	N	F	2019-01-15 00:00	E01010927	Calderdale 009A	16996	6	27065	9	24322	8	639	1	19461	6	20421	7
{8355F009-B39B-55C5-E053-6B04A8C0D090}	HX1 2YJ	198500	T	N	F	2019-01-09 00:00	E01010969	Calderdale 016A	18647	6	19630	6	16351	5	15424	5	15152	5	24787	8
{8355F009-B39D-55C5-E053-6B04A8C0D090}	LS28 6FA	228000	S	N	F	2019-02-04 00:00	E01011596	Leeds 062D	25901	8	29495	9	26309	9	13001	4	21919	7	25788	8
{8355F009-B39F-55C5-E053-6B04A8C0D090}	LS29 7EY	295000	T	N	F	2019-02-15 00:00	E01010769	Bradford 003C	26788	9	25317	8	25648	8	21930	7	20276	7	28466	9
{8355F009-B3A0-55C5-E053-6B04A8C0D090}	LS12 6BU	116500	F	N	L	2019-01-02 00:00	E01011734	Leeds 083A	18442	6	22720	7	24200	8	9328	3	16034	5	19159	6
{8355F009-B3A1-55C5-E053-6B04A8C0D090}	LS15 0NJ	199999	D	N	F	2019-01-29 00:00	E01011616	Leeds 072A	1152	1	2008	1	967	1	1243	1	1393	1	1468	1
{8355F009-B3A2-55C5-E053-6B04A8C0D090}	WF11 8QF	65000	S	N	F	2019-01-22 00:00	E01011804	Wakefield 011B	9611	3	13401	5	9617	3	6109	2	10573	4	3589	2
{8355F009-B3A3-55C5-E053-6B04A8C0D090}	LS19 7QA	88000	T	N	F	2019-01-29 00:00	E01011276	Leeds 011C	19771	7	22476	7	22088	7	7815	3	16183	5	27979	9
{8355F009-B3A4-55C5-E053-6B04A8C0D090}	BD12 0EX	130000	T	N	F	2019-01-29 00:00	E01010741	Bradford 059A	9746	3	15713	5	13633	5	331	1	14652	5	13410	5
{8355F009-B3A6-55C5-E053-6B04A8C0D090}	LS25 1NJ	105000	F	N	L	2019-02-21 00:00	E01011403	Leeds 074D	22784	7	20898	7	21351	7	22708	7	7911	3	27069	9
{8355F009-B3A9-55C5-E053-6B04A8C0D090}	LS10 4GA	208000	T	N	F	2019-02-01 00:00	E01011490	Leeds 099A	18717	6	18474	6	22994	8	4424	2	14765	5	20853	7
{8355F009-B3AB-55C5-E053-6B04A8C0D090}	LS18 5JR	330000	S	N	F	2019-02-01 00:00	E01011455	Leeds 021A	30741	10	32494	10	32706	10	23614	8	26076	8	31363	10
{8355F009-B3AC-55C5-E053-6B04A8C0D090}	BD16 2PR	210000	T	N	F	2019-01-25 00:00	E01010584	Bradford 015D	7752	3	9289	3	9481	3	3413	2	5868	2	8072	3
{8355F009-B3AD-55C5-E053-6B04A8C0D090}	WF10 5GU	200000	D	N	L	2019-01-18 00:00	E01011775	Wakefield 024A	21047	7	20122	7	16080	5	21214	7	20231	7	20059	7
{8355F009-B3B1-55C5-E053-6B04A8C0D090}	LS10 4SW	35000	F	N	L	2019-01-18 00:00	E01011490	Leeds 099A	18717	6	18474	6	22994	8	4424	2	14765	5	20853	7
{8355F009-B3B2-55C5-E053-6B04A8C0D090}	HX1 2YH	167500	T	N	F	2019-01-31 00:00	E01010969	Calderdale 016A	18647	6	19630	6	16351	5	15424	5	15152	5	24787	8
{8355F009-B3B3-55C5-E053-6B04A8C0D090}	LS6 3BY	150000	S	N	F	2019-02-08 00:00	E01011441	Leeds 044E	18606	6	19652	6	20884	7	14304	5	11452	4	25230	8
{8355F009-B3B5-55C5-E053-6B04A8C0D090}	BD22 0QG	203000	T	N	F	2019-01-18 00:00	E01010722	Bradford 014A	2233	1	3886	2	3623	2	177	1	3809	2	2580	1
{8355F009-B3B7-55C5-E053-6B04A8C0D090}	WF7 6FG	124850	T	N	F	2019-01-28 00:00	E01011778	Wakefield 024D	11184	4	12037	4	8731	3	12353	4	7945	3	5360	2
{8355F009-B3B8-55C5-E053-6B04A8C0D090}	BD13 2FQ	208000	S	N	F	2019-01-04 00:00	E01010752	Bradford 058A	6179	2	10508	4	8629	3	1529	1	6432	2	14222	5
{8355F009-B3B9-55C5-E053-6B04A8C0D090}	HD7 5RD	127000	T	N	L	2019-02-08 00:00	E01011077	Kirklees 045A	12793	4	17371	6	18115	6	10005	4	15742	5	16773	6
{8355F009-B3BB-55C5-E053-6B04A8C0D090}	HX5 0DX	175000	T	N	F	2019-02-08 00:00	E01010894	Calderdale 025D	3768	2	4313	2	5243	2	7830	3	7794	3	3754	2
{8355F009-B3BC-55C5-E053-6B04A8C0D090}	LS6 4AE	107000	F	N	L	2019-01-14 00:00	E01011692	Leeds 109D	22555	7	26422	9	26267	8	6531	2	22772	7	32673	10
{8355F009-B3BD-55C5-E053-6B04A8C0D090}	LS10 4FP	95000	F	N	L	2019-02-08 00:00	E01011490	Leeds 099A	18717	6	18474	6	22994	8	4424	2	14765	5	20853	7
{8355F009-B3BE-55C5-E053-6B04A8C0D090}	WF8 3AD	320000	D	N	F	2019-01-31 00:00	E01011849	Wakefield 034E	21151	7	21988	7	19979	7	11313	4	18198	6	25486	8
{8355F009-B3BF-55C5-E053-6B04A8C0D090}	HX2 8AF	130000	S	N	F	2019-01-31 00:00	E01010939	Calderdale 005B	16387	5	23239	8	18862	6	1208	1	13984	5	20582	7
{8355F009-B3C0-55C5-E053-6B04A8C0D090}	BD5 7HT	64000	S	N	F	2019-01-29 00:00	E01010736	Bradford 048D	2289	1	4456	2	5429	2	1774	1	7504	3	314	1
{8355F009-B3C4-55C5-E053-6B04A8C0D090}	CR5 2YS	715000	O	N	F	2019-01-11 00:00	E01001023	Croydon 041C	11765	4	11262	4	9844	3	13090	4	14367	5	22719	7
{8355F009-B3C5-55C5-E053-6B04A8C0D090}	SW1V 4NU	1800000	T	N	F	2019-02-04 00:00	E01004751	Westminster 022C	24060	8	22710	7	25729	8	10587	4	31316	10	30756	10
{8355F009-B74F-55C5-E053-6B04A8C0D090}	MK16 8TH	335000	O	N	F	2019-02-01 00:00	E01016788	Milton Keynes 003C	27067	9	28885	9	29173	9	23939	8	28286	9	21439	7
{8355F009-B751-55C5-E053-6B04A8C0D090}	MK13 8BS	145000	F	N	L	2019-01-18 00:00	E01016724	Milton Keynes 013D	12503	4	10822	4	13122	4	9358	3	11901	4	11627	4
{8355F009-B752-55C5-E053-6B04A8C0D090}	LU6 2RP	475000	S	N	F	2019-02-06 00:00	E01017658	Aylesbury Vale 009D	26147	8	26237	8	30293	10	28462	9	28123	9	27678	9
{8355F009-B753-55C5-E053-6B04A8C0D090}	MK11 1NN	210000	S	N	F	2019-01-31 00:00	E01016817	Milton Keynes 010B	17886	6	14425	5	15901	5	15536	5	21533	7	20248	7
{8355F009-B754-55C5-E053-6B04A8C0D090}	HP10 8AD	250000	O	N	F	2019-01-18 00:00	E01017784	Chiltern 013E	31154	10	32073	10	32162	10	31069	10	32737	10	30390	10
{8355F009-B755-55C5-E053-6B04A8C0D090}	HP14 4NN	820000	O	N	F	2019-02-15 00:00	E01017872	Wycombe 003D	31474	10	31784	10	32168	10	32788	10	32397	10	29760	10
{8355F009-B758-55C5-E053-6B04A8C0D090}	MK2 3NU	172000	T	N	F	2019-02-05 00:00	E01016744	Milton Keynes 032C	3158	1	2827	1	5532	2	6787	3	7779	3	3468	2
{8355F009-B759-55C5-E053-6B04A8C0D090}	MK11 3HE	240000	O	N	F	2019-02-12 00:00	E01016810	Milton Keynes 012A	3304	2	4139	2	2368	1	10525	4	4831	2	5284	2
{8355F009-B75A-55C5-E053-6B04A8C0D090}	SL3 6BH	280000	F	N	L	2019-02-15 00:00	E01017834	South Bucks 005D	19887	7	25098	8	28772	9	4877	2	29961	10	17100	6
{8355F009-B75C-55C5-E053-6B04A8C0D090}	MK13 0EQ	170000	T	N	F	2019-02-08 00:00	E01016835	Milton Keynes 006D	6027	2	6268	2	7152	3	7212	3	6210	2	4986	2
{8355F009-B75D-55C5-E053-6B04A8C0D090}	SL0 9JQ	13021125	O	N	F	2019-02-08 00:00	E01017827	South Bucks 008D	18326	6	18529	6	20080	7	8841	3	26903	9	12038	4
{8355F009-B75E-55C5-E053-6B04A8C0D090}	HP11 2TL	725000	D	N	F	2019-02-11 00:00	E01017838	Wycombe 015C	24120	8	18290	6	24536	8	24000	8	30357	10	19917	7
{8355F009-B760-55C5-E053-6B04A8C0D090}	HP12 3BD	450000	O	N	F	2019-02-07 00:00	E01017904	Wycombe 013B	12505	4	8580	3	10926	4	17203	6	21030	7	7350	3
{8355F009-B761-55C5-E053-6B04A8C0D090}	MK6 2PJ	250000	T	N	F	2019-02-01 00:00	E01016725	Milton Keynes 021A	9735	3	8015	3	11590	4	10635	4	15350	5	10714	4
{8355F009-B762-55C5-E053-6B04A8C0D090}	MK14 7LJ	220000	T	N	F	2019-01-29 00:00	E01016768	Milton Keynes 014D	15798	5	14323	5	18635	6	7754	3	18484	6	16589	6
{8355F009-B763-55C5-E053-6B04A8C0D090}	HP8 4SL	1900000	O	N	F	2019-01-16 00:00	E01017762	Chiltern 008A	31470	10	32827	10	32739	10	31874	10	32734	10	32533	10
{8355F009-B764-55C5-E053-6B04A8C0D090}	HP12 3SL	19625000	O	N	F	2019-01-18 00:00	E01017840	Wycombe 015E	27778	9	21954	7	21758	7	29557	9	28027	9	24656	8
{8355F009-B765-55C5-E053-6B04A8C0D090}	MK14 6HJ	235000	O	N	F	2019-02-15 00:00	E01016771	Milton Keynes 005E	15264	5	11494	4	13454	5	19167	6	10576	4	15045	5
{8355F009-B766-55C5-E053-6B04A8C0D090}	HP27 9DE	472000	O	N	F	2019-01-11 00:00	E01017931	Wycombe 001C	23821	8	21642	7	15666	5	25371	8	26712	9	15335	5
{8355F009-B767-55C5-E053-6B04A8C0D090}	MK4 2EH	235500	T	N	F	2019-02-08 00:00	E01016748	Milton Keynes 028A	24481	8	21647	7	22429	7	21890	7	19373	6	19940	7
{8355F009-B768-55C5-E053-6B04A8C0D090}	MK14 7BH	117500	F	N	L	2019-02-01 00:00	E01016718	Milton Keynes 014A	5811	2	7032	3	6351	2	5290	2	8751	3	6956	3
{8355F009-B769-55C5-E053-6B04A8C0D090}	MK10 0BT	24945550	O	N	F	2019-01-10 00:00	E01016783	Milton Keynes 017A	23978	8	21543	7	22150	7	20486	7	25278	8	22818	7
{8355F009-B76A-55C5-E053-6B04A8C0D090}	MK13 8RE	147000	F	N	L	2019-01-18 00:00	E01016724	Milton Keynes 013D	12503	4	10822	4	13122	4	9358	3	11901	4	11627	4
{8355F009-B76B-55C5-E053-6B04A8C0D090}	HP6 5RW	325000	O	N	F	2019-01-31 00:00	E01017778	Chiltern 001D	28662	9	29893	10	29786	10	25229	8	32163	10	30382	10
{8355F009-B76D-55C5-E053-6B04A8C0D090}	MK18 1LU	202000	S	N	F	2019-01-15 00:00	E01017646	Aylesbury Vale 002C	20258	7	15647	5	18225	6	17094	6	21356	7	15301	5
{8355F009-B76F-55C5-E053-6B04A8C0D090}	MK18 1WD	250000	T	N	F	2019-01-17 00:00	E01017645	Aylesbury Vale 002B	13183	5	12624	4	17576	6	13463	5	7478	3	12449	4
{8355F009-B770-55C5-E053-6B04A8C0D090}	MK3 7AN	230000	S	N	F	2019-02-05 00:00	E01016738	Milton Keynes 027B	8416	3	6975	3	9130	3	15435	5	9415	3	5111	2
{8355F009-B771-55C5-E053-6B04A8C0D090}	HP10 9AR	321000	D	N	F	2019-01-31 00:00	E01017865	Wycombe 018B	32278	10	31142	10	30885	10	32340	10	31165	10	28597	9
{8355F009-B772-55C5-E053-6B04A8C0D090}	RG9 6SR	2800000	O	N	F	2019-02-05 00:00	E01017878	Wycombe 007D	18842	6	32189	10	32579	10	29225	9	32635	10	32123	10
{8355F009-B773-55C5-E053-6B04A8C0D090}	SL7 1DQ	700000	S	N	F	2019-02-01 00:00	E01017895	Wycombe 023A	28329	9	20972	7	21500	7	27501	9	30387	10	30081	10
{8355F009-B774-55C5-E053-6B04A8C0D090}	SL7 1QX	2100000	O	N	F	2019-01-18 00:00	E01017896	Wycombe 023B	32818	10	32504	10	32760	10	28731	9	32378	10	32711	10
{8355F009-BA50-55C5-E053-6B04A8C0D090}	PL13 2JE	285000	O	N	F	2019-02-15 00:00	E01018762	Cornwall 037A	10232	4	15695	5	13709	5	26228	8	10483	4	15890	5
{8355F009-BA66-55C5-E053-6B04A8C0D090}	TR10 9EW	16250	O	N	L	2019-01-18 00:00	E01018834	Cornwall 060A	17676	6	14368	5	14406	5	29457	9	17438	6	15852	5
{8355F009-BA68-55C5-E053-6B04A8C0D090}	TR11 5PU	535000	O	N	F	2019-01-18 00:00	E01018879	Cornwall 066A	20297	7	23554	8	18961	6	31805	10	23102	8	29412	9
{8355F009-BA6D-55C5-E053-6B04A8C0D090}	TR14 0FJ	198000	S	Y	F	2019-01-04 00:00	E01018865	Cornwall 052A	4895	2	7527	3	4010	2	8947	3	6370	2	8377	3
{8355F009-BA6F-55C5-E053-6B04A8C0D090}	TR4 8RH	5000	O	N	F	2019-01-31 00:00	E01018829	Cornwall 056C	10011	4	11924	4	11393	4	29426	9	16769	6	24268	8
{8355F009-BA71-55C5-E053-6B04A8C0D090}	TR7 2SY	165000	T	N	F	2019-01-25 00:00	E01019023	Cornwall 021F	21519	7	18819	6	23237	8	30699	10	21068	7	11531	4
{8355F009-BA72-55C5-E053-6B04A8C0D090}	EX23 9RQ	125000	S	N	F	2019-01-23 00:00	E01018943	Cornwall 002A	12514	4	15202	5	15457	5	31268	10	24972	8	14854	5
{8355F009-BA73-55C5-E053-6B04A8C0D090}	TR7 3EH	700000	O	N	F	2019-01-22 00:00	E01019049	Cornwall 018B	13536	5	11287	4	9839	3	25576	8	19132	6	10985	4
{8355F009-BA76-55C5-E053-6B04A8C0D090}	PL27 6LU	615000	D	N	F	2019-02-11 00:00	E01033289	Cornwall 007E	14501	5	16889	6	17738	6	25584	8	23880	8	17823	6
{8355F009-BA79-55C5-E053-6B04A8C0D090}	TR26 3HX	45100	O	N	L	2019-01-04 00:00	E01018987	Cornwall 058C	12046	4	19101	6	15747	5	29885	10	21498	7	27643	9
{8355F009-BA7A-55C5-E053-6B04A8C0D090}	PL11 2AA	100000	O	N	F	2019-01-18 00:00	E01018797	Cornwall 029A	5989	2	5298	2	4216	2	15493	5	2413	1	8906	3
{8355F009-BA7C-55C5-E053-6B04A8C0D090}	PL28 8PY	15000	O	N	L	2019-01-19 00:00	E01018954	Cornwall 008A	11274	4	16985	6	21128	7	30870	10	22232	7	16329	5
{8355F009-BA7D-55C5-E053-6B04A8C0D090}	TR4 9NF	1600000	O	N	F	2019-01-23 00:00	E01018843	Cornwall 033C	12688	4	18783	6	15821	5	29052	9	20240	7	26825	9
{8355F009-BA7E-55C5-E053-6B04A8C0D090}	TR4 8QG	1020000	O	N	F	2019-02-04 00:00	E01018820	Cornwall 047D	13320	5	13910	5	16386	5	29138	9	18329	6	21485	7
{8355F009-BA7F-55C5-E053-6B04A8C0D090}	PL15 9DY	25500	O	N	F	2019-02-11 00:00	E01018950	Cornwall 005E	11253	4	10279	4	8430	3	21042	7	16834	6	14332	5
{8355F009-BA80-55C5-E053-6B04A8C0D090}	TR2 5BG	40000	O	N	F	2019-01-21 00:00	E01018849	Cornwall 048D	16230	5	15840	5	20152	7	31141	10	21819	7	21522	7
{8355F009-BA81-55C5-E053-6B04A8C0D090}	LA14 1NA	47500	T	N	F	2019-02-06 00:00	E01019158	Barrow-in-Furness 008E	1301	1	3964	2	1620	1	2972	1	344	1	4645	2
{8355F009-BA83-55C5-E053-6B04A8C0D090}	CA28 6SB	153000	D	N	F	2019-01-30 00:00	E01019262	Copeland 003B	24449	8	28625	9	21659	7	32007	10	15225	5	24211	8
{8355F009-BA84-55C5-E053-6B04A8C0D090}	LA9 6ND	305000	O	N	F	2019-01-14 00:00	E01019365	South Lakeland 003C	23276	8	27110	9	25377	8	22637	7	24031	8	22001	7
{8355F009-BA85-55C5-E053-6B04A8C0D090}	LA13 0JY	150000	S	N	F	2019-01-11 00:00	E01019179	Barrow-in-Furness 006E	28119	9	27672	9	26671	9	30770	10	11371	4	26776	9
{8355F009-BA86-55C5-E053-6B04A8C0D090}	LA12 8EE	350000	T	N	F	2019-01-14 00:00	E01019351	South Lakeland 008D	19141	6	27945	9	30031	10	32698	10	26226	8	24448	8
{8355F009-BA88-55C5-E053-6B04A8C0D090}	CA13 9YD	690000	O	N	F	2019-01-22 00:00	E01019090	Allerdale 007E	15065	5	28772	9	31101	10	24115	8	25116	8	29648	10
{8355F009-BA89-55C5-E053-6B04A8C0D090}	CA28 8QN	72000	T	N	F	2019-01-25 00:00	E01019285	Copeland 003D	6060	2	8560	3	4382	2	23102	8	1899	1	3753	2
{8355F009-BA8A-55C5-E053-6B04A8C0D090}	LA6 2NP	2100000	O	N	F	2019-01-31 00:00	E01019373	South Lakeland 009B	25655	8	30586	10	27981	9	24349	8	23782	8	28080	9
{8355F009-BA8C-55C5-E053-6B04A8C0D090}	CA11 0SJ	5000	O	N	F	2019-02-05 00:00	E01019339	Eden 005D	15915	5	27773	9	30590	10	29318	9	31136	10	21985	7
{8355F009-BA8D-55C5-E053-6B04A8C0D090}	LA9 4SX	425000	O	N	F	2019-01-25 00:00	E01019360	South Lakeland 004A	15960	5	16223	5	13491	5	16807	6	16460	6	27278	9
{8355F009-BA8F-55C5-E053-6B04A8C0D090}	LA14 1BN	60000	T	N	F	2019-01-14 00:00	E01019141	Barrow-in-Furness 008A	522	1	1091	1	526	1	18371	6	238	1	1486	1
{8355F009-BA90-55C5-E053-6B04A8C0D090}	LA9 5HG	1300000	O	N	F	2019-01-10 00:00	E01019369	South Lakeland 006D	25540	8	21788	7	17071	6	32807	10	20422	7	27711	9
{8355F009-BE62-55C5-E053-6B04A8C0D090}	DE23 4DY	200000	S	N	F	2019-02-01 00:00	E01013545	Derby 021E	16844	6	14353	5	9936	4	27529	9	11337	4	24681	8
{8355F009-BE63-55C5-E053-6B04A8C0D090}	DE23 6TE	152000	S	N	F	2019-02-08 00:00	E01013485	Derby 016C	3040	1	2187	1	6323	2	5214	2	8596	3	605	1
{8355F009-BE64-55C5-E053-6B04A8C0D090}	DE23 8AG	3020000	O	N	F	2019-02-05 00:00	E01013571	Derby 023B	3641	2	4606	2	6717	3	3138	1	3210	1	2666	1
{8355F009-BE65-55C5-E053-6B04A8C0D090}	DE5 8RH	300000	T	N	F	2019-01-18 00:00	E01019449	Amber Valley 011E	26559	9	26407	9	28907	9	27343	9	27799	9	20698	7
{8355F009-BE66-55C5-E053-6B04A8C0D090}	DE22 4GJ	128000	S	N	F	2019-01-31 00:00	E01013552	Derby 009C	5283	2	4969	2	3820	2	16895	6	3081	1	3379	2
{8355F009-BE69-55C5-E053-6B04A8C0D090}	DE22 3SX	110000	O	N	F	2019-01-14 00:00	E01013456	Derby 013C	1646	1	2642	1	2310	1	3962	2	803	1	2090	1
{8355F009-BE6A-55C5-E053-6B04A8C0D090}	DE7 8EF	135000	O	N	F	2019-01-24 00:00	E01019640	Erewash 016C	31553	10	30810	10	28014	9	31943	10	19937	7	23540	8
{8355F009-BE6B-55C5-E053-6B04A8C0D090}	DE3 0QH	143000	S	N	F	2019-01-31 00:00	E01013556	Derby 015A	30611	10	30659	10	28566	9	31265	10	18350	6	27283	9
{8355F009-BE6D-55C5-E053-6B04A8C0D090}	DE4 4NR	300	O	N	F	2019-01-29 00:00	E01019636	Derbyshire Dales 007D	22198	7	17123	6	17864	6	28457	9	21759	7	16497	6
{8355F009-BE6E-55C5-E053-6B04A8C0D090}	DE24 9NE	60000	T	N	F	2019-02-21 00:00	E01013588	Derby 029E	4494	2	4863	2	4039	2	2353	1	4684	2	5685	2
{8355F009-BE6F-55C5-E053-6B04A8C0D090}	DE23 1JG	415000	D	N	F	2019-02-12 00:00	E01013488	Derby 022A	26785	9	25287	8	26195	8	28031	9	21631	7	24741	8
{8355F009-BE72-55C5-E053-6B04A8C0D090}	DE22 3SE	85000	T	N	F	2019-01-28 00:00	E01013460	Derby 013E	9920	4	12560	4	18733	6	5013	2	8676	3	12441	4
{8355F009-BE78-55C5-E053-6B04A8C0D090}	NG10 3ND	280000	O	N	F	2019-02-20 00:00	E01019705	Erewash 015D	23720	8	19953	7	21939	7	26753	9	20602	7	14340	5
{8355F009-BE7A-55C5-E053-6B04A8C0D090}	S41 7ST	759300	D	N	F	2019-02-14 00:00	E01033387	Chesterfield 010F	16005	5	20751	7	22127	7	5362	2	10410	4	19725	7
{8355F009-BE7B-55C5-E053-6B04A8C0D090}	S41 0JH	276000	O	N	F	2019-01-18 00:00	E01019798	North East Derbyshire 007A	16654	6	12692	4	14496	5	17219	6	13230	5	16298	5
{8355F009-BE7C-55C5-E053-6B04A8C0D090}	DE56 0DL	245000	D	N	F	2019-01-11 00:00	E01019410	Amber Valley 011A	24307	8	27520	9	24945	8	29963	10	18698	6	20455	7
{8355F009-BE7E-55C5-E053-6B04A8C0D090}	S42 6AW	855000	O	N	F	2019-02-01 00:00	E01019769	North East Derbyshire 010A	21554	7	26294	9	26699	9	30229	10	24072	8	24883	8
{8355F009-BE7F-55C5-E053-6B04A8C0D090}	DE7 9JJ	185000	S	N	F	2019-02-05 00:00	E01019639	Erewash 016B	14261	5	9388	3	12056	4	18705	6	17213	6	6662	3
{8355F009-BE80-55C5-E053-6B04A8C0D090}	DE55 2FB	247000	D	N	F	2019-01-14 00:00	E01019513	Bolsover 010D	20273	7	21307	7	20148	7	27576	9	12287	4	14167	5
{8355F009-BE81-55C5-E053-6B04A8C0D090}	DE55 2EP	62450	T	N	F	2019-01-25 00:00	E01019517	Bolsover 010E	26261	8	27003	9	21327	7	27114	9	19521	6	18589	6
{8355F009-BE82-55C5-E053-6B04A8C0D090}	DE7 4JB	50000	F	N	L	2019-01-09 00:00	E01019669	Erewash 007D	14064	5	14912	5	11919	4	26061	8	11317	4	6518	2
{8355F009-BE83-55C5-E053-6B04A8C0D090}	S40 2HR	79000	T	N	F	2019-01-28 00:00	E01019578	Chesterfield 013D	499	1	590	1	157	1	16684	6	160	1	410	1
{8355F009-BE84-55C5-E053-6B04A8C0D090}	DE7 9JE	130000	S	N	F	2019-01-18 00:00	E01019640	Erewash 016C	31553	10	30810	10	28014	9	31943	10	19937	7	23540	8
{8355F009-BE85-55C5-E053-6B04A8C0D090}	DE4 5ND	280000	O	N	F	2019-01-31 00:00	E01019627	Derbyshire Dales 005E	27445	9	23414	8	24854	8	32451	10	20804	7	25009	8
{8355F009-BE88-55C5-E053-6B04A8C0D090}	DE55 2FJ	290000	D	N	F	2019-01-31 00:00	E01019513	Bolsover 010D	20273	7	21307	7	20148	7	27576	9	12287	4	14167	5
{8355F009-BE89-55C5-E053-6B04A8C0D090}	SK23 7QA	36000	O	N	F	2019-02-05 00:00	E01019766	High Peak 005E	23260	8	18231	6	17015	6	32070	10	17955	6	24769	8
{8355F009-BE8A-55C5-E053-6B04A8C0D090}	DE23 8LL	110000	T	N	F	2019-01-31 00:00	E01033167	Derby 018G	666	1	531	1	849	1	15785	5	314	1	1025	1
{8355F009-BE8B-55C5-E053-6B04A8C0D090}	DE7 8AZ	160000	O	N	F	2019-01-30 00:00	E01019672	Erewash 003E	7556	3	8691	3	6890	3	8761	3	7466	3	8677	3
{8355F009-BE8C-55C5-E053-6B04A8C0D090}	DE65 6NL	225000	S	N	F	2019-01-31 00:00	E01019840	South Derbyshire 002A	24635	8	20834	7	20003	7	27805	9	13865	5	23787	8
{8355F009-BE8D-55C5-E053-6B04A8C0D090}	NG10 2AL	115000	T	N	F	2019-02-19 00:00	E01019682	Erewash 012D	4792	2	6111	2	5379	2	5524	2	3971	2	5163	2
{8355F009-BE8E-55C5-E053-6B04A8C0D090}	DE11 7NN	113500	O	N	F	2019-01-28 00:00	E01019859	South Derbyshire 007E	22175	7	19739	7	18994	6	31164	10	19580	6	12075	4
{8355F009-BE91-55C5-E053-6B04A8C0D090}	DE4 2LY	625000	O	N	F	2019-01-11 00:00	E01019630	Derbyshire Dales 004C	23247	8	21759	7	24082	8	32133	10	27396	9	22545	7
{8355F009-B3C7-55C5-E053-6B04A8C0D090}	W11 1EA	495000	F	N	F	2019-02-11 00:00	E01002829	Kensington and Chelsea 004A	6055	2	5953	2	5290	2	5417	2	15925	5	26510	9
{8355F009-B3C8-55C5-E053-6B04A8C0D090}	SW17 7HS	60000	O	N	F	2019-01-25 00:00	E01004547	Wandsworth 029C	14054	5	11970	4	9731	3	13408	5	17573	6	26413	9
{8355F009-B3C9-55C5-E053-6B04A8C0D090}	SE18 3PA	395000	T	N	F	2019-02-01 00:00	E01001681	Greenwich 020C	15871	5	14617	5	12837	4	7796	3	18238	6	25212	8
{8355F009-B3CA-55C5-E053-6B04A8C0D090}	EC1M 4HF	14250000	O	N	F	2019-01-17 00:00	E01033490	Islington 022H	14740	5	17753	6	25893	8	22894	7	20295	7	22056	7
{8355F009-B3CB-55C5-E053-6B04A8C0D090}	SE27 0BT	800000	S	N	F	2019-01-02 00:00	E01003080	Lambeth 027B	15676	5	15404	5	17616	6	10982	4	22367	7	27806	9
{8355F009-B3CC-55C5-E053-6B04A8C0D090}	W6 7BJ	4850000	O	N	F	2019-01-30 00:00	E01001869	Hammersmith and Fulham 010D	19649	6	21171	7	24758	8	11543	4	19135	6	31077	10
{8355F009-B3CD-55C5-E053-6B04A8C0D090}	N16 5JA	1160000	F	N	F	2019-01-31 00:00	E01001807	Hackney 003D	8454	3	7503	3	11046	4	13951	5	17169	6	17732	6
{8355F009-B3CE-55C5-E053-6B04A8C0D090}	E5 9JW	850000	T	N	F	2019-02-19 00:00	E01001792	Hackney 011A	6784	3	7382	3	11517	4	2053	1	9890	4	21014	7
{8355F009-B3CF-55C5-E053-6B04A8C0D090}	NW1 9RZ	16000	O	N	F	2019-01-10 00:00	E01000865	Camden 015B	20799	7	23464	8	26045	8	10136	4	19996	7	30190	10
{8355F009-B3D0-55C5-E053-6B04A8C0D090}	SW8 3BS	47300	O	N	F	2019-01-31 00:00	E01003037	Lambeth 013A	4779	2	4842	2	5369	2	6026	2	1674	1	21711	7
{8355F009-B3D1-55C5-E053-6B04A8C0D090}	SW17 7RH	722500	O	N	F	2019-02-14 00:00	E01004548	Wandsworth 029D	16560	6	15021	5	20576	7	14336	5	16228	5	26594	9
{8355F009-B3D2-55C5-E053-6B04A8C0D090}	SW17 9RZ	425000	T	N	F	2019-02-01 00:00	E01004526	Wandsworth 035B	12185	4	10506	4	16773	6	4292	2	14572	5	25118	8
{8355F009-B3D3-55C5-E053-6B04A8C0D090}	SE6 2AA	670000	D	N	F	2019-01-25 00:00	E01003325	Lewisham 018D	5420	2	7071	3	9575	3	5199	2	9366	3	14492	5
{8355F009-B3D4-55C5-E053-6B04A8C0D090}	SW1Y 5JG	81650	O	N	F	2019-01-31 00:00	E01004736	Westminster 018C	24862	8	32833	10	32702	10	16515	6	32709	10	28230	9
{8355F009-B3D5-55C5-E053-6B04A8C0D090}	SE24 9DH	10000	O	N	F	2019-01-25 00:00	E01003170	Lambeth 025E	21658	7	21062	7	26971	9	7187	3	23701	8	32259	10
{8355F009-B3D6-55C5-E053-6B04A8C0D090}	N7 6QA	880000	O	N	F	2019-01-03 00:00	E01002731	Islington 007B	11066	4	13149	5	19620	6	2432	1	18071	6	21595	7
{8355F009-B3D7-55C5-E053-6B04A8C0D090}	SE6 3JH	450000	S	N	F	2019-01-30 00:00	E01003318	Lewisham 020B	2640	1	5204	2	3041	1	2034	1	6051	2	17392	6
{8355F009-B3D8-55C5-E053-6B04A8C0D090}	SW18 2DB	700000	T	N	F	2019-01-14 00:00	E01004512	Wandsworth 019B	21622	7	21567	7	20867	7	12722	4	24404	8	28723	9
{8355F009-B3D9-55C5-E053-6B04A8C0D090}	SE26 5HB	250000	O	N	F	2019-02-18 00:00	E01003327	Lewisham 035B	17542	6	18963	6	19867	7	13215	5	22380	7	24599	8
{8355F009-B3DD-55C5-E053-6B04A8C0D090}	SW17 0EA	480000	S	N	F	2019-02-06 00:00	E01004610	Wandsworth 033C	14415	5	16033	5	20527	7	2074	1	23157	8	27178	9
{8355F009-B3DE-55C5-E053-6B04A8C0D090}	W6 8QX	2500000	O	N	F	2019-01-31 00:00	E01001891	Hammersmith and Fulham 018B	22811	7	29294	9	31391	10	17189	6	23251	8	15532	5
{8355F009-B3DF-55C5-E053-6B04A8C0D090}	NW3 2PN	1000000	O	N	F	2019-02-05 00:00	E01000897	Camden 008D	30122	10	30822	10	30989	10	13725	5	32674	10	31154	10
{8355F009-B3E1-55C5-E053-6B04A8C0D090}	N5 2AA	900000	O	N	F	2019-02-06 00:00	E01002744	Islington 009D	16228	5	14540	5	14547	5	13672	5	13266	5	25176	8
{8355F009-B3E2-55C5-E053-6B04A8C0D090}	W12 8AB	815000	T	N	F	2019-01-14 00:00	E01001943	Hammersmith and Fulham 004A	6650	3	9442	3	9741	3	1401	1	10684	4	26495	9
{8355F009-B3E3-55C5-E053-6B04A8C0D090}	SE5 8DL	680000	O	N	F	2019-01-09 00:00	E01004045	Southwark 027A	9397	3	5685	2	7497	3	24340	8	14852	5	18230	6
{8355F009-B3E5-55C5-E053-6B04A8C0D090}	SW2 1AJ	14000	O	N	F	2019-01-25 00:00	E01003050	Lambeth 016B	9105	3	13413	5	19767	7	601	1	15213	5	19237	6
{8355F009-B3E6-55C5-E053-6B04A8C0D090}	NW10 6AJ	21800	O	N	F	2019-01-25 00:00	E01001877	Hammersmith and Fulham 001D	6532	2	6516	2	6699	3	6019	2	9633	3	22569	7
{8355F009-B3E8-55C5-E053-6B04A8C0D090}	SW15 6SQ	595000	O	N	F	2019-02-08 00:00	E01004506	Wandsworth 011A	25152	8	25163	8	30303	10	18135	6	28600	9	25710	8
{8355F009-B3E9-55C5-E053-6B04A8C0D090}	NW8 9SD	52500	O	N	F	2019-01-21 00:00	E01004726	Westminster 003C	25261	8	26899	9	29640	10	20009	7	32628	10	28805	9
{8355F009-B3EA-55C5-E053-6B04A8C0D090}	N6 5NY	290000	F	N	L	2019-01-11 00:00	E01002006	Haringey 035B	18324	6	19006	6	21368	7	15019	5	23437	8	31199	10
{8355F009-B3EB-55C5-E053-6B04A8C0D090}	N22 6QS	3750	O	N	F	2019-02-01 00:00	E01002088	Haringey 013C	11266	4	14260	5	21387	7	4388	2	21957	7	8984	3
{8355F009-B3EF-55C5-E053-6B04A8C0D090}	TW5 9JW	260000	T	N	F	2019-01-25 00:00	E01002634	Hounslow 005B	6742	3	5499	2	6546	2	7905	3	17761	6	9703	3
{8355F009-B776-55C5-E053-6B04A8C0D090}	MK14 6TD	305118	D	N	F	2019-02-08 00:00	E01016804	Milton Keynes 009D	9002	3	7015	3	9308	3	20859	7	9873	4	7474	3
{8355F009-B779-55C5-E053-6B04A8C0D090}	MK17 0HX	1845000	O	N	F	2019-01-31 00:00	E01017696	Aylesbury Vale 003D	32384	10	29793	10	30177	10	30205	10	31719	10	25604	8
{8355F009-B77A-55C5-E053-6B04A8C0D090}	HP11 2HL	1080000	O	N	F	2019-01-11 00:00	E01017837	Wycombe 015B	12204	4	11192	4	14573	5	5068	2	17040	6	16809	6
{8355F009-B77B-55C5-E053-6B04A8C0D090}	MK16 9HN	1005000	O	N	F	2019-01-25 00:00	E01016803	Milton Keynes 002F	14553	5	22468	7	28854	9	17418	6	25018	8	20417	7
{8355F009-B77C-55C5-E053-6B04A8C0D090}	HP21 7SD	240000	T	N	F	2019-02-08 00:00	E01017634	Aylesbury Vale 015B	18084	6	18161	6	25534	8	3768	2	27255	9	15249	5
{8355F009-B77D-55C5-E053-6B04A8C0D090}	SL7 2BP	625000	O	N	F	2019-02-08 00:00	E01017894	Wycombe 022F	32682	10	32280	10	31043	10	24601	8	31971	10	32376	10
{8355F009-B77E-55C5-E053-6B04A8C0D090}	HP11 2RS	475000	O	N	F	2019-01-31 00:00	E01017837	Wycombe 015B	12204	4	11192	4	14573	5	5068	2	17040	6	16809	6
{8355F009-B77F-55C5-E053-6B04A8C0D090}	MK10 9GQ	248400	T	N	F	2019-01-21 00:00	E01016783	Milton Keynes 017A	23978	8	21543	7	22150	7	20486	7	25278	8	22818	7
{8355F009-B780-55C5-E053-6B04A8C0D090}	HP20 2LH	365000	O	N	F	2019-02-08 00:00	E01032961	Aylesbury Vale 015F	15712	5	15723	5	19670	6	5566	2	19898	7	11415	4
{8355F009-B781-55C5-E053-6B04A8C0D090}	HP5 3RB	4075000	O	N	F	2019-01-11 00:00	E01017750	Chiltern 001A	23928	8	29980	10	28971	9	25103	8	32723	10	30062	10
{8355F009-B783-55C5-E053-6B04A8C0D090}	MK3 6LL	160000	T	N	F	2019-02-06 00:00	E01016741	Milton Keynes 027E	7093	3	6683	3	8075	3	9931	4	11401	4	2556	1
{8355F009-B784-55C5-E053-6B04A8C0D090}	MK2 3NU	190000	T	N	F	2019-02-05 00:00	E01016744	Milton Keynes 032C	3158	1	2827	1	5532	2	6787	3	7779	3	3468	2
{8355F009-B785-55C5-E053-6B04A8C0D090}	HP21 7SE	639000	D	N	F	2019-01-25 00:00	E01017634	Aylesbury Vale 015B	18084	6	18161	6	25534	8	3768	2	27255	9	15249	5
{8355F009-B786-55C5-E053-6B04A8C0D090}	MK11 2BA	165000	T	N	F	2019-01-31 00:00	E01016811	Milton Keynes 012B	2496	1	2807	1	4155	2	8531	3	12371	4	873	1
{8355F009-B787-55C5-E053-6B04A8C0D090}	MK6 4HR	143000	T	N	F	2019-02-12 00:00	E01016842	Milton Keynes 023B	1211	1	1514	1	1773	1	2633	1	3694	2	817	1
{8355F009-B788-55C5-E053-6B04A8C0D090}	HP15 6AX	45000	O	N	F	2019-01-31 00:00	E01032609	Chiltern 013F	27637	9	20492	7	22802	7	29594	10	25559	8	20967	7
{8355F009-B789-55C5-E053-6B04A8C0D090}	HP11 2PU	630000	O	N	F	2019-02-08 00:00	E01017837	Wycombe 015B	12204	4	11192	4	14573	5	5068	2	17040	6	16809	6
{8355F009-B78B-55C5-E053-6B04A8C0D090}	MK6 4HX	153000	T	N	F	2019-02-08 00:00	E01016845	Milton Keynes 018C	1595	1	1676	1	2188	1	5203	2	2580	1	942	1
{8355F009-B78D-55C5-E053-6B04A8C0D090}	MK3 6AR	261000	S	N	F	2019-01-30 00:00	E01016834	Milton Keynes 029E	8425	3	7171	3	9315	3	21178	7	9302	3	3268	1
{8355F009-B792-55C5-E053-6B04A8C0D090}	SL1 8ET	1200000	O	N	F	2019-01-31 00:00	E01017803	South Bucks 006A	22264	7	29489	9	29500	9	7512	3	31563	10	28880	9
{8355F009-B793-55C5-E053-6B04A8C0D090}	MK6 3AD	488500	O	N	F	2019-02-07 00:00	E01033498	Milton Keynes 023F	5584	2	8167	3	5800	2	2390	1	8847	3	12743	4
{8355F009-B796-55C5-E053-6B04A8C0D090}	MK17 0FD	3000	O	N	F	2019-02-05 00:00	E01017672	Aylesbury Vale 003B	27254	9	26206	8	29939	10	31097	10	26277	9	28673	9
{8355F009-B797-55C5-E053-6B04A8C0D090}	HP13 6LJ	69960	O	N	L	2019-02-01 00:00	E01017839	Wycombe 015D	18218	6	19385	6	15143	5	9975	4	26406	9	20508	7
{8355F009-B798-55C5-E053-6B04A8C0D090}	MK1 1HW	655000	O	N	F	2019-01-29 00:00	E01016716	Milton Keynes 030C	11200	4	9051	3	9397	3	14046	5	11998	4	10641	4
{8355F009-B799-55C5-E053-6B04A8C0D090}	SL7 2DH	1663500	O	N	F	2019-01-18 00:00	E01017892	Wycombe 022D	32689	10	32796	10	32484	10	31582	10	32491	10	32770	10
{8355F009-B79C-55C5-E053-6B04A8C0D090}	MK3 7NE	130000	F	N	L	2019-02-01 00:00	E01016741	Milton Keynes 027E	7093	3	6683	3	8075	3	9931	4	11401	4	2556	1
{8355F009-B79D-55C5-E053-6B04A8C0D090}	MK12 5GH	285000	S	N	F	2019-01-11 00:00	E01016840	Milton Keynes 010D	23265	8	20684	7	25901	8	12916	4	29120	9	17867	6
{8355F009-B79E-55C5-E053-6B04A8C0D090}	MK9 3FY	194119	O	N	L	2019-01-23 00:00	E01016768	Milton Keynes 014D	15798	5	14323	5	18635	6	7754	3	18484	6	16589	6
{8355F009-B7A1-55C5-E053-6B04A8C0D090}	MK8 1AB	266250	T	N	F	2019-02-06 00:00	E01033525	Milton Keynes 019H	17851	6	14457	5	17469	6	18176	6	18890	6	19235	6
{8355F009-BA91-55C5-E053-6B04A8C0D090}	CA22 2EU	82000	T	N	F	2019-02-07 00:00	E01019272	Copeland 006B	7265	3	6731	3	4707	2	28212	9	4679	2	3165	1
{8355F009-BA93-55C5-E053-6B04A8C0D090}	CA14 1QU	175000	D	N	F	2019-02-08 00:00	E01019124	Allerdale 008E	30357	10	30826	10	25262	8	32452	10	21918	7	22182	7
{8355F009-BA94-55C5-E053-6B04A8C0D090}	CA1 3TR	127500	S	N	L	2019-02-11 00:00	E01019251	Carlisle 004F	32375	10	28534	9	29870	10	31960	10	27583	9	29763	10
{8355F009-BA95-55C5-E053-6B04A8C0D090}	LA14 2AA	69000	T	N	F	2019-02-08 00:00	E01019142	Barrow-in-Furness 008B	695	1	1879	1	1748	1	1479	1	353	1	2263	1
{8355F009-BA96-55C5-E053-6B04A8C0D090}	LA22 0NH	285000	F	N	L	2019-01-31 00:00	E01019356	South Lakeland 007A	17453	6	26652	9	23167	8	31231	10	27665	9	24822	8
{8355F009-BA97-55C5-E053-6B04A8C0D090}	LA10 5RQ	525000	O	N	F	2019-02-07 00:00	E01019384	South Lakeland 009C	18416	6	28652	9	27965	9	31682	10	30002	10	20761	7
{8355F009-BA98-55C5-E053-6B04A8C0D090}	CA4 0JT	495000	O	N	F	2019-01-31 00:00	E01019315	Eden 002A	17191	6	23584	8	25383	8	32828	10	23922	8	19970	7
{8355F009-BA99-55C5-E053-6B04A8C0D090}	LA9 6LZ	450000	O	N	F	2019-01-31 00:00	E01019365	South Lakeland 003C	23276	8	27110	9	25377	8	22637	7	24031	8	22001	7
{8355F009-BA9B-55C5-E053-6B04A8C0D090}	CA13 0AX	203199	S	N	F	2019-02-07 00:00	E01019087	Allerdale 007D	31497	10	31205	10	28586	9	32735	10	25301	8	29620	10
{8355F009-BA9C-55C5-E053-6B04A8C0D090}	LA9 4NF	955000	O	N	F	2019-02-06 00:00	E01019370	South Lakeland 003D	23740	8	24565	8	20310	7	25111	8	24300	8	23544	8
{8355F009-BA9E-55C5-E053-6B04A8C0D090}	CA25 5ND	50000	T	N	F	2019-01-25 00:00	E01019267	Copeland 004F	3311	2	3980	2	1410	1	19475	6	1680	1	2437	1
{8355F009-BAA0-55C5-E053-6B04A8C0D090}	CA14 5XJ	240000	O	N	F	2019-01-25 00:00	E01019268	Copeland 001A	13037	4	19334	6	15331	5	28164	9	8398	3	16764	6
{8355F009-BAA1-55C5-E053-6B04A8C0D090}	LA6 2NP	2100000	O	N	F	2019-01-31 00:00	E01019373	South Lakeland 009B	25655	8	30586	10	27981	9	24349	8	23782	8	28080	9
{8355F009-BAA2-55C5-E053-6B04A8C0D090}	CA16 6EP	625000	O	N	F	2019-01-22 00:00	E01019340	Eden 007E	12037	4	22561	7	16739	6	27457	9	23546	8	15324	5
{8355F009-BAA3-55C5-E053-6B04A8C0D090}	CA15 7RB	500000	O	N	F	2019-01-25 00:00	E01019096	Allerdale 004C	19053	6	15736	5	11028	4	25405	8	18132	6	13316	5
{8355F009-BAA4-55C5-E053-6B04A8C0D090}	LA22 9DG	252500	O	N	F	2019-01-25 00:00	E01019374	South Lakeland 001A	23496	8	22023	7	23977	8	25116	8	21275	7	14825	5
{8355F009-BAA5-55C5-E053-6B04A8C0D090}	CA3 8HP	1165000	O	N	F	2019-01-10 00:00	E01019206	Carlisle 006B	6285	2	7136	3	4480	2	6034	2	4084	2	20834	7
{8355F009-BAA7-55C5-E053-6B04A8C0D090}	CA6 6DS	50000	O	N	F	2019-02-07 00:00	E01019229	Carlisle 001D	10872	4	19528	6	18832	6	32488	10	20748	7	14990	5
{8355F009-BAA8-55C5-E053-6B04A8C0D090}	LA12 8RB	50000	O	N	L	2019-02-05 00:00	E01019386	South Lakeland 007C	16067	5	27608	9	26021	8	31544	10	27991	9	22692	7
{8355F009-BAAA-55C5-E053-6B04A8C0D090}	LA22 9AD	37500	O	N	L	2019-01-28 00:00	E01019374	South Lakeland 001A	23496	8	22023	7	23977	8	25116	8	21275	7	14825	5
{8355F009-BAAB-55C5-E053-6B04A8C0D090}	CA11 7SF	220000	O	N	F	2019-02-08 00:00	E01019329	Eden 004D	23126	8	28451	9	25940	8	28109	9	22575	7	25792	8
{8355F009-BAAE-55C5-E053-6B04A8C0D090}	LA23 1BA	418000	T	N	F	2019-02-05 00:00	E01019395	South Lakeland 001D	21344	7	21526	7	21150	7	28954	9	22495	7	16056	5
{8355F009-BAAF-55C5-E053-6B04A8C0D090}	LA11 7HH	67000	F	N	L	2019-01-31 00:00	E01019354	South Lakeland 013C	19441	6	17222	6	14574	5	28548	9	14964	5	22758	7
{8355F009-BAB0-55C5-E053-6B04A8C0D090}	LA8 9HN	300000	O	N	L	2019-02-08 00:00	E01019346	South Lakeland 003A	18879	6	22397	7	24582	8	32496	10	22982	7	17577	6
{8355F009-BAB1-55C5-E053-6B04A8C0D090}	CA11 9TG	160000	O	N	F	2019-02-07 00:00	E01019338	Eden 002D	14896	5	26423	9	30270	10	32741	10	27600	9	20724	7
{8355F009-BAB2-55C5-E053-6B04A8C0D090}	CA15 8DL	20000	O	N	F	2019-02-15 00:00	E01019098	Allerdale 005C	12458	4	12480	4	10885	4	20888	7	10697	4	5919	2
{8355F009-BAC8-55C5-E053-6B04A8C0D090}	LA10 5AD	130000	T	N	F	2019-02-01 00:00	E01019385	South Lakeland 009D	19049	6	17027	6	15935	5	30100	10	17670	6	20241	7
{8355F009-BACA-55C5-E053-6B04A8C0D090}	LA6 2NP	2100000	O	N	F	2019-01-31 00:00	E01019373	South Lakeland 009B	25655	8	30586	10	27981	9	24349	8	23782	8	28080	9
{8355F009-BAD5-55C5-E053-6B04A8C0D090}	CA24 3LT	110000	O	N	F	2019-01-02 00:00	E01019273	Copeland 006C	18868	6	22090	7	19232	6	31405	10	10789	4	18340	6
{8355F009-BAD8-55C5-E053-6B04A8C0D090}	CA8 2DZ	1300000	O	N	F	2019-01-11 00:00	E01019225	Carlisle 002D	14837	5	22505	7	21847	7	31513	10	23682	8	23462	8
{8355F009-BAD9-55C5-E053-6B04A8C0D090}	LA23 2AB	389999	O	N	F	2019-01-31 00:00	E01019398	South Lakeland 002D	19854	7	21251	7	21358	7	24101	8	22929	7	7708	3
{8355F009-BADA-55C5-E053-6B04A8C0D090}	CA11 8BQ	224950	O	N	F	2019-02-01 00:00	E01019331	Eden 004F	22999	8	19730	7	22040	7	30757	10	24113	8	9728	3
{8355F009-BADC-55C5-E053-6B04A8C0D090}	CA28 7UX	130000	O	N	F	2019-01-29 00:00	E01019280	Copeland 002B	943	1	1890	1	117	1	1547	1	88	1	7129	3
{8355F009-BADD-55C5-E053-6B04A8C0D090}	CA4 8BD	340000	S	N	F	2019-01-31 00:00	E01019251	Carlisle 004F	32375	10	28534	9	29870	10	31960	10	27583	9	29763	10
{8355F009-BADE-55C5-E053-6B04A8C0D090}	CA25 5QH	85000	S	N	F	2019-01-14 00:00	E01019265	Copeland 004D	5872	2	8381	3	3153	1	14022	5	1727	1	7349	3
{8355F009-BDDF-55C5-E053-6B04A8C0D090}	SR4 6NW	55000	T	N	F	2019-01-28 00:00	E01008757	Sunderland 015A	5051	2	4454	2	3829	2	2127	1	2676	1	11172	4
{8355F009-BDE0-55C5-E053-6B04A8C0D090}	DH9 8NQ	68000	T	N	F	2019-01-28 00:00	E01020625	County Durham 009B	10306	4	8301	3	5611	2	15794	5	8025	3	10203	4
{8355F009-BDE1-55C5-E053-6B04A8C0D090}	DH9 8NQ	90000	D	N	F	2019-01-28 00:00	E01020625	County Durham 009B	10306	4	8301	3	5611	2	15794	5	8025	3	10203	4
{8355F009-BDE2-55C5-E053-6B04A8C0D090}	SR7 0HL	50000	F	N	L	2019-01-18 00:00	E01020787	County Durham 016E	8076	3	5781	2	3965	2	13595	5	7221	3	8797	3
{8355F009-BDE3-55C5-E053-6B04A8C0D090}	DL3 9ER	77500	O	N	F	2019-02-15 00:00	E01012365	Darlington 007D	20993	7	22181	7	16888	6	4191	2	16202	5	24326	8
{8355F009-BDE5-55C5-E053-6B04A8C0D090}	DH7 7EF	95000	T	N	F	2019-01-25 00:00	E01020714	County Durham 026D	19376	6	20013	7	15002	5	10410	4	12757	4	24963	8
{8355F009-BDE6-55C5-E053-6B04A8C0D090}	DL14 9AQ	90000	S	N	F	2019-02-08 00:00	E01020895	County Durham 057C	4345	2	3946	2	2932	1	7004	3	2727	1	3384	2
{8355F009-BDE7-55C5-E053-6B04A8C0D090}	DL12 0QE	345000	O	N	F	2019-02-01 00:00	E01020865	County Durham 065C	13603	5	20030	7	18880	6	22455	7	13129	4	18308	6
{8355F009-BDE8-55C5-E053-6B04A8C0D090}	DL1 4DF	230000	O	N	F	2019-02-15 00:00	E01012340	Darlington 012D	8316	3	8137	3	9312	3	1607	1	7459	3	6367	2
{8355F009-BDEB-55C5-E053-6B04A8C0D090}	DL16 7QF	135000	S	N	F	2019-01-25 00:00	E01020836	County Durham 052E	8726	3	8345	3	6951	3	3985	2	6250	2	8415	3
{8355F009-BDEC-55C5-E053-6B04A8C0D090}	DH7 9YU	88000	T	N	F	2019-01-25 00:00	E01020658	County Durham 024B	6776	3	6784	3	4814	2	10079	4	2099	1	8350	3
{8355F009-BDED-55C5-E053-6B04A8C0D090}	SR1 3JP	210000	O	N	F	2019-01-31 00:00	E01008703	Sunderland 013B	3277	1	5273	2	4161	2	1717	1	126	1	8011	3
{8355F009-BDEF-55C5-E053-6B04A8C0D090}	DL4 1JD	39950	T	N	F	2019-01-18 00:00	E01020801	County Durham 059A	9721	3	7038	3	7491	3	3474	2	11127	4	14438	5
{8355F009-BDF0-55C5-E053-6B04A8C0D090}	DL2 2BU	115000	S	N	F	2019-02-01 00:00	E01012338	Darlington 015A	16670	6	16775	6	13295	5	6999	3	16638	6	21677	7
{8355F009-BDF1-55C5-E053-6B04A8C0D090}	DL1 5HW	120000	F	N	L	2019-02-22 00:00	E01033484	Darlington 008F	1586	1	2318	1	669	1	480	1	822	1	11766	4
{8355F009-BDF2-55C5-E053-6B04A8C0D090}	DL14 7EW	70000	O	N	L	2019-01-11 00:00	E01020868	County Durham 055A	6624	3	7640	3	4206	2	1450	1	4628	2	16839	6
{8355F009-BDF3-55C5-E053-6B04A8C0D090}	DH8 7EF	103000	T	N	F	2019-01-28 00:00	E01020650	County Durham 012A	14196	5	11143	4	11114	4	22352	7	10171	4	11514	4
{8355F009-BDF4-55C5-E053-6B04A8C0D090}	DH6 2LB	185000	D	N	F	2019-02-01 00:00	E01020760	County Durham 034A	8326	3	9845	3	4615	2	7766	3	2730	1	11999	4
{8355F009-BDF5-55C5-E053-6B04A8C0D090}	DL17 0EQ	165000	S	N	F	2019-02-22 00:00	E01020803	County Durham 053B	15038	5	13034	4	10371	4	12081	4	11116	4	12579	4
{8355F009-BDF6-55C5-E053-6B04A8C0D090}	DH1 3RF	830000	D	N	F	2019-02-11 00:00	E01020713	County Durham 033E	31636	10	32606	10	32483	10	30417	10	30334	10	32769	10
{8355F009-BDF7-55C5-E053-6B04A8C0D090}	DL17 0EQ	180000	D	N	F	2019-02-08 00:00	E01020803	County Durham 053B	15038	5	13034	4	10371	4	12081	4	11116	4	12579	4
{8355F009-BDF8-55C5-E053-6B04A8C0D090}	DH9 8DY	45000	T	N	F	2019-01-31 00:00	E01020638	County Durham 006B	8550	3	5664	2	5461	2	12860	4	5980	2	8892	3
{8355F009-BDF9-55C5-E053-6B04A8C0D090}	DH7 7RG	180000	D	N	F	2019-01-24 00:00	E01020715	County Durham 031C	11156	4	9050	3	6917	3	10737	4	9137	3	9693	3
{8355F009-BDFA-55C5-E053-6B04A8C0D090}	DH7 7RG	155000	D	N	F	2019-01-24 00:00	E01020715	County Durham 031C	11156	4	9050	3	6917	3	10737	4	9137	3	9693	3
{8355F009-BDFB-55C5-E053-6B04A8C0D090}	SR2 9NA	80000	T	N	F	2019-01-18 00:00	E01008779	Sunderland 024C	10221	4	8839	3	8166	3	6921	3	4984	2	13028	4
{8355F009-BDFD-55C5-E053-6B04A8C0D090}	DL14 7BW	31500	F	N	L	2019-02-05 00:00	E01020872	County Durham 056C	11087	4	10352	4	8918	3	5510	2	5141	2	16544	6
{8355F009-BE00-55C5-E053-6B04A8C0D090}	DH7 9FF	390000	D	N	F	2019-01-29 00:00	E01020660	County Durham 024D	13583	5	13921	5	11371	4	14694	5	11332	4	14012	5
{8355F009-BE01-55C5-E053-6B04A8C0D090}	DH7 9FF	390000	O	N	F	2019-01-29 00:00	E01020660	County Durham 024D	13583	5	13921	5	11371	4	14694	5	11332	4	14012	5
{8355F009-BE03-55C5-E053-6B04A8C0D090}	SR7 7TZ	115000	S	N	F	2019-02-01 00:00	E01020740	County Durham 017A	14665	5	14158	5	11034	4	12563	4	7333	3	11461	4
{8355F009-BE04-55C5-E053-6B04A8C0D090}	SR7 7TZ	115000	S	N	F	2019-02-01 00:00	E01020740	County Durham 017A	14665	5	14158	5	11034	4	12563	4	7333	3	11461	4
{8355F009-BE05-55C5-E053-6B04A8C0D090}	DL13 5ND	110000	O	N	F	2019-01-25 00:00	E01020864	County Durham 064G	15678	5	16863	6	14797	5	27213	9	16204	5	16924	6
{8355F009-BE24-55C5-E053-6B04A8C0D090}	DL16 7FZ	100000	T	Y	F	2019-01-03 00:00	E01020820	County Durham 049C	4984	2	3852	2	3991	2	5336	2	3379	2	4833	2
{8355F009-BE2D-55C5-E053-6B04A8C0D090}	SR7 9DE	39950	T	N	F	2019-01-09 00:00	E01033161	County Durham 021D	14725	5	15572	5	13656	5	5542	2	7235	3	12707	4
{8355F009-B3F0-55C5-E053-6B04A8C0D090}	NW2 2RJ	328000	F	N	L	2019-01-04 00:00	E01000143	Barnet 041D	7380	3	4534	2	6262	2	5800	2	17289	6	16148	5
{8355F009-B3F1-55C5-E053-6B04A8C0D090}	TW14 9BW	285000	F	N	L	2019-02-15 00:00	E01002590	Hounslow 022C	15491	5	18181	6	21107	7	11017	4	18459	6	10804	4
{8355F009-B3F4-55C5-E053-6B04A8C0D090}	TW13 7QA	275000	F	N	L	2019-02-15 00:00	E01002615	Hounslow 026E	5539	2	5324	2	7011	3	10233	4	11063	4	8312	3
{8355F009-B3F5-55C5-E053-6B04A8C0D090}	TW1 1DG	18200000	O	N	F	2019-01-18 00:00	E01003867	Richmond upon Thames 011A	22428	7	21692	7	21259	7	12292	4	28969	9	31438	10
{8355F009-B3F6-55C5-E053-6B04A8C0D090}	N8 9NL	450000	T	N	L	2019-01-17 00:00	E01002059	Haringey 028C	13380	5	10304	4	11686	4	13195	5	17450	6	29101	9
{8355F009-B3F7-55C5-E053-6B04A8C0D090}	W4 5DY	370000	F	N	L	2019-01-18 00:00	E01001376	Ealing 040B	11416	4	7281	3	8441	3	17584	6	19691	6	20932	7
{8355F009-B3F8-55C5-E053-6B04A8C0D090}	N22 5BY	295000	F	N	L	2019-01-17 00:00	E01002100	Haringey 008B	6336	2	7288	3	9437	3	4141	2	16335	5	8907	3
{8355F009-B3F9-55C5-E053-6B04A8C0D090}	W4 2RB	475000	F	N	L	2019-01-29 00:00	E01002572	Hounslow 007B	7879	3	5815	2	7673	3	12416	4	8490	3	15172	5
{8355F009-B3FB-55C5-E053-6B04A8C0D090}	TW13 6UB	250000	F	N	L	2019-01-30 00:00	E01002610	Hounslow 028C	9741	3	8162	3	11035	4	7424	3	15017	5	8368	3
{8355F009-B3FC-55C5-E053-6B04A8C0D090}	HA4 9LT	1175000	O	N	F	2019-02-01 00:00	E01002417	Hillingdon 008B	28823	9	28289	9	29691	10	12019	4	29836	10	29199	9
{8355F009-B3FD-55C5-E053-6B04A8C0D090}	UB3 2TP	370000	S	N	F	2019-01-04 00:00	E01002402	Hillingdon 024C	11133	4	10274	4	11437	4	7099	3	19588	6	12411	4
{8355F009-B3FE-55C5-E053-6B04A8C0D090}	N17 6LP	130000	F	N	L	2019-01-30 00:00	E01002089	Haringey 013D	2662	1	1073	1	2043	1	14776	5	11269	4	5560	2
{8355F009-B401-55C5-E053-6B04A8C0D090}	HA6 1QL	210000	O	N	L	2019-01-18 00:00	E01002483	Hillingdon 002D	25352	8	22589	7	21574	7	22612	7	22704	7	28878	9
{8355F009-B402-55C5-E053-6B04A8C0D090}	TW5 9PN	208000	F	N	L	2019-01-11 00:00	E01002633	Hounslow 005A	4802	2	3598	2	5775	2	15771	5	8977	3	8875	3
{8355F009-B406-55C5-E053-6B04A8C0D090}	EN1 2NW	9000	O	N	L	2019-01-29 00:00	E01001405	Enfield 015A	22069	7	17645	6	24418	8	22899	7	21676	7	27570	9
{8355F009-B409-55C5-E053-6B04A8C0D090}	UB6 9RU	1000	O	N	L	2019-01-08 00:00	E01001258	Ealing 010B	18071	6	16502	6	17384	6	19924	7	23954	8	20624	7
{8355F009-B40E-55C5-E053-6B04A8C0D090}	NW2 5AP	340000	F	N	L	2019-01-18 00:00	E01000639	Brent 022C	12728	4	12639	4	18679	6	4948	2	27175	9	20520	7
{8355F009-B40F-55C5-E053-6B04A8C0D090}	NW10 5JA	38500	O	N	F	2019-02-15 00:00	E01000531	Brent 033B	10593	4	8043	3	10822	4	16348	5	20245	7	21313	7
{8355F009-B411-55C5-E053-6B04A8C0D090}	TW13 4PA	1000	O	N	L	2019-02-15 00:00	E01002616	Hounslow 027E	16858	6	16016	5	19278	6	17469	6	16383	5	11425	4
{8355F009-B412-55C5-E053-6B04A8C0D090}	E3 4PG	325000	F	N	L	2019-02-06 00:00	E01004268	Tower Hamlets 012E	6121	2	3680	2	6345	2	19864	7	6762	3	11128	4
{8355F009-B413-55C5-E053-6B04A8C0D090}	E5 8NB	247992	F	N	L	2019-01-25 00:00	E01001770	Hackney 010E	6158	2	5430	2	9153	3	6146	2	8154	3	13477	5
{8355F009-B415-55C5-E053-6B04A8C0D090}	TW8 0AP	424000	O	N	L	2019-02-15 00:00	E01033082	Hounslow 003G	10592	4	9912	4	12465	4	5762	2	15374	5	20886	7
{8355F009-B416-55C5-E053-6B04A8C0D090}	EN2 7AQ	336000	F	N	L	2019-01-30 00:00	E01001457	Enfield 010A	20056	7	17805	6	19171	6	29179	9	25147	8	24702	8
{8355F009-B417-55C5-E053-6B04A8C0D090}	HA0 1BN	1320000	O	N	F	2019-01-30 00:00	E01000475	Brent 029C	13473	5	13267	5	19273	6	23209	8	28063	9	18822	6
{8355F009-B419-55C5-E053-6B04A8C0D090}	UB6 0NY	305000	T	N	F	2019-02-01 00:00	E01001307	Ealing 002A	23210	8	22225	7	27549	9	17560	6	30411	10	22160	7
{8355F009-B41A-55C5-E053-6B04A8C0D090}	TW7 7QQ	323500	F	N	L	2019-01-11 00:00	E01002673	Hounslow 020E	2294	1	1421	1	2734	1	8717	3	4688	2	6787	3
{8355F009-B41C-55C5-E053-6B04A8C0D090}	HA4 8JY	5000	O	N	L	2019-01-21 00:00	E01002535	Hillingdon 007E	26634	9	23190	8	26887	9	16664	6	27499	9	29068	9
{8355F009-B41D-55C5-E053-6B04A8C0D090}	TW8 0GR	285000	F	N	L	2019-01-18 00:00	E01002568	Hounslow 003D	7180	3	6014	2	11064	4	6260	2	6566	2	17222	6
{8355F009-B7A7-55C5-E053-6B04A8C0D090}	HP13 5DQ	531000	O	N	F	2019-01-29 00:00	E01017837	Wycombe 015B	12204	4	11192	4	14573	5	5068	2	17040	6	16809	6
{8355F009-B7C1-55C5-E053-6B04A8C0D090}	HP11 2FP	228000	F	Y	L	2019-01-11 00:00	E01017837	Wycombe 015B	12204	4	11192	4	14573	5	5068	2	17040	6	16809	6
{8355F009-B7C2-55C5-E053-6B04A8C0D090}	MK3 7DT	280000	S	N	F	2019-01-21 00:00	E01016833	Milton Keynes 029D	28431	9	28525	9	30304	10	25177	8	27389	9	24012	8
{8355F009-B7C5-55C5-E053-6B04A8C0D090}	MK18 7BB	230000	S	N	F	2019-01-08 00:00	E01017644	Aylesbury Vale 002A	28060	9	26956	9	27295	9	27306	9	28741	9	19951	7
{8355F009-B7C9-55C5-E053-6B04A8C0D090}	MK18 3AT	300000	T	N	F	2019-01-17 00:00	E01017736	Aylesbury Vale 005B	22732	7	15276	5	16174	5	24334	8	24646	8	19336	6
{8355F009-B7CD-55C5-E053-6B04A8C0D090}	CB4 3JL	600000	S	N	F	2019-01-28 00:00	E01017955	Cambridge 005A	30984	10	28342	9	32328	10	22507	7	29576	10	32562	10
{8355F009-B7CE-55C5-E053-6B04A8C0D090}	PE2 5FW	148500	T	N	F	2019-02-07 00:00	E01015637	Peterborough 021A	1519	1	2297	1	2666	1	3218	1	1816	1	1569	1
{8355F009-B7D1-55C5-E053-6B04A8C0D090}	PE28 5QU	100000	O	N	F	2019-02-14 00:00	E01018192	Huntingdonshire 004B	20346	7	18470	6	19953	7	23423	8	27071	9	16138	5
{8355F009-B7D2-55C5-E053-6B04A8C0D090}	CB6 1RY	216000	O	N	F	2019-02-08 00:00	E01018027	East Cambridgeshire 003A	29025	9	27394	9	28511	9	29450	9	30686	10	25775	8
{8355F009-B7D3-55C5-E053-6B04A8C0D090}	CB7 5QQ	725000	D	N	F	2019-01-30 00:00	E01018035	East Cambridgeshire 007B	18031	6	20187	7	21721	7	30594	10	26337	9	16164	5
{8355F009-B7D4-55C5-E053-6B04A8C0D090}	PE7 3YQ	135000	S	N	F	2019-01-21 00:00	E01018214	Huntingdonshire 001C	15402	5	11243	4	11143	4	18685	6	20006	7	7556	3
{8355F009-B7D5-55C5-E053-6B04A8C0D090}	CB21 6AN	1400000	O	N	F	2019-01-21 00:00	E01018288	South Cambridgeshire 017C	29835	10	26853	9	28910	9	31614	10	30437	10	29188	9
{8355F009-B7D8-55C5-E053-6B04A8C0D090}	CB8 8AW	295000	S	N	F	2019-02-08 00:00	E01032611	East Cambridgeshire 011D	29194	9	32166	10	32491	10	30873	10	32003	10	27496	9
{8355F009-B7DA-55C5-E053-6B04A8C0D090}	CB8 8AT	450000	D	N	F	2019-01-18 00:00	E01018019	East Cambridgeshire 011B	31590	10	30298	10	28725	9	31009	10	24073	8	25025	8
{8355F009-B7DD-55C5-E053-6B04A8C0D090}	PE1 2QY	95500	F	N	L	2019-01-18 00:00	E01015655	Peterborough 014E	14158	5	15835	5	19582	6	3299	2	15522	5	15880	5
{8355F009-B7DE-55C5-E053-6B04A8C0D090}	PE16 6DX	170000	T	N	F	2019-02-18 00:00	E01018102	Fenland 011B	10930	4	9891	4	9126	3	9374	3	10616	4	7218	3
{8355F009-B7DF-55C5-E053-6B04A8C0D090}	PE1 1PW	275000	O	N	F	2019-02-15 00:00	E01015599	Peterborough 014A	4770	2	6436	2	11553	4	1760	1	8793	3	1400	1
{8355F009-B7E0-55C5-E053-6B04A8C0D090}	PE29 3QS	337000	S	N	F	2019-01-11 00:00	E01018138	Huntingdonshire 012A	13178	5	16996	6	13646	5	12741	4	18963	6	13402	5
{8355F009-B7E2-55C5-E053-6B04A8C0D090}	PE13 2PG	110000	T	N	F	2019-01-25 00:00	E01033112	Fenland 003I	3986	2	9043	3	6745	3	1396	1	2762	1	1742	1
{8355F009-B7E3-55C5-E053-6B04A8C0D090}	PE13 2UQ	160000	D	N	F	2019-02-15 00:00	E01018069	Fenland 003A	15384	5	17642	6	16985	6	18334	6	6005	2	10695	4
{8355F009-B7E4-55C5-E053-6B04A8C0D090}	SG8 5QN	895000	O	N	F	2019-02-01 00:00	E01018275	South Cambridgeshire 013D	26937	9	27713	9	29127	9	22874	7	30921	10	22505	7
{8355F009-B7E5-55C5-E053-6B04A8C0D090}	PE15 8SS	130000	T	N	F	2019-01-31 00:00	E01018084	Fenland 005D	12357	4	13390	5	10863	4	26894	9	7143	3	10945	4
{8355F009-B7E6-55C5-E053-6B04A8C0D090}	PE13 1DP	180000	F	N	F	2019-01-22 00:00	E01033112	Fenland 003I	3986	2	9043	3	6745	3	1396	1	2762	1	1742	1
{8355F009-B7E7-55C5-E053-6B04A8C0D090}	PE2 6SN	190000	S	N	F	2019-02-01 00:00	E01015644	Peterborough 018B	18165	6	16966	6	19089	6	28146	9	14083	5	12795	4
{8355F009-B7E8-55C5-E053-6B04A8C0D090}	PE2 8SS	165000	S	N	F	2019-02-15 00:00	E01015667	Peterborough 019A	9290	3	10271	4	14712	5	1253	1	7324	3	9174	3
{8355F009-BAE3-55C5-E053-6B04A8C0D090}	CA13 0QE	3000	O	N	F	2019-02-13 00:00	E01019090	Allerdale 007E	15065	5	28772	9	31101	10	24115	8	25116	8	29648	10
{8355F009-BAE4-55C5-E053-6B04A8C0D090}	CA11 8HR	330000	O	N	F	2019-02-15 00:00	E01019333	Eden 003C	8695	3	9831	3	7368	3	15123	5	10600	4	4234	2
{8355F009-BAE5-55C5-E053-6B04A8C0D090}	CA14 2AD	145000	O	N	F	2019-02-22 00:00	E01019121	Allerdale 009E	1912	1	4380	2	1222	1	5445	2	1280	1	2576	1
{8355F009-BAE7-55C5-E053-6B04A8C0D090}	LA23 2JS	400000	O	N	F	2019-02-06 00:00	E01019396	South Lakeland 002B	26961	9	21964	7	23519	8	28276	9	29506	9	21441	7
{8355F009-BAE8-55C5-E053-6B04A8C0D090}	CA11 9BY	157500	T	N	F	2019-02-15 00:00	E01019336	Eden 003E	17200	6	18333	6	16441	6	21682	7	18669	6	11343	4
{8355F009-BAE9-55C5-E053-6B04A8C0D090}	CA16 6TU	118000	O	N	F	2019-02-06 00:00	E01019307	Eden 006B	25163	8	23117	8	23075	8	27985	9	24956	8	13820	5
{8355F009-BAEB-55C5-E053-6B04A8C0D090}	CA14 2NR	72000	O	N	L	2019-01-31 00:00	E01019120	Allerdale 009D	8979	3	12241	4	10393	4	8163	3	9864	4	6602	3
{8355F009-BAEC-55C5-E053-6B04A8C0D090}	LA14 5PA	110000	T	N	F	2019-01-14 00:00	E01019167	Barrow-in-Furness 005A	11735	4	17788	6	13432	5	25697	8	3091	1	18233	6
{8355F009-BAED-55C5-E053-6B04A8C0D090}	LA12 0JB	155000	T	N	F	2019-01-25 00:00	E01019378	South Lakeland 014A	24852	8	24333	8	22100	7	32801	10	24426	8	26902	9
{8355F009-BAEE-55C5-E053-6B04A8C0D090}	LA9 4RR	165000	T	N	F	2019-02-01 00:00	E01019370	South Lakeland 003D	23740	8	24565	8	20310	7	25111	8	24300	8	23544	8
{8355F009-BAEF-55C5-E053-6B04A8C0D090}	LA14 5AP	82500	F	N	F	2019-02-15 00:00	E01019171	Barrow-in-Furness 005E	6781	3	11127	4	6971	3	21207	7	1591	1	15962	5
{8355F009-BAF0-55C5-E053-6B04A8C0D090}	LA18 5EE	90750	T	N	F	2019-02-01 00:00	E01019289	Copeland 008C	8008	3	8099	3	5496	2	32045	10	5373	2	4209	2
{8355F009-BAF1-55C5-E053-6B04A8C0D090}	LA14 2HZ	55000	T	N	F	2019-02-18 00:00	E01019143	Barrow-in-Furness 008C	99	1	601	1	225	1	1712	1	44	1	1661	1
{8355F009-BAF3-55C5-E053-6B04A8C0D090}	LA14 1AY	41000	T	N	F	2019-01-14 00:00	E01019142	Barrow-in-Furness 008B	695	1	1879	1	1748	1	1479	1	353	1	2263	1
{8355F009-BAF4-55C5-E053-6B04A8C0D090}	LA18 4NF	650000	O	N	F	2019-02-21 00:00	E01019283	Copeland 008B	12225	4	19889	7	12952	4	31371	10	2340	1	8918	3
{8355F009-BAF5-55C5-E053-6B04A8C0D090}	LA15 8AN	105000	S	N	F	2019-01-31 00:00	E01019147	Barrow-in-Furness 001D	12184	4	18178	6	14066	5	27216	9	5769	2	13104	4
{85866A64-AC7F-143F-E053-6B04A8C06A15}	CO5 7PU	258000	T	N	F	2019-02-18 00:00	E01021694	Colchester 019D	15200	5	23254	8	16915	6	17077	6	22454	7	20485	7
{85866A64-AC80-143F-E053-6B04A8C06A15}	CM18 7QJ	236000	T	N	F	2019-03-08 00:00	E01021862	Harlow 011A	11311	4	9927	4	11739	4	15640	5	9097	3	6640	3
{85866A64-AC81-143F-E053-6B04A8C06A15}	CM9 6BW	285000	S	N	F	2019-02-15 00:00	E01021894	Maldon 005B	17349	6	12657	4	13781	5	25725	8	16392	5	9688	3
{85866A64-AC82-143F-E053-6B04A8C06A15}	IG10 1PR	255000	F	N	L	2019-02-12 00:00	E01021786	Epping Forest 012A	29157	9	28037	9	27865	9	17841	6	32212	10	22634	7
{85866A64-AC85-143F-E053-6B04A8C06A15}	CM2 0ND	450000	F	N	F	2019-02-28 00:00	E01033140	Chelmsford 010F	14057	5	13069	4	15939	5	1340	1	16716	6	28235	9
{85866A64-AC86-143F-E053-6B04A8C06A15}	SS17 7JU	185000	F	N	L	2019-02-21 00:00	E01015987	Thurrock 002C	7637	3	7020	3	7204	3	12902	4	6874	3	4201	2
{85866A64-AC87-143F-E053-6B04A8C06A15}	CM3 5ZQ	164000	T	N	L	2019-02-19 00:00	E01021607	Chelmsford 020C	25705	8	22354	7	24577	8	27730	9	27405	9	16916	6
{85866A64-AC89-143F-E053-6B04A8C06A15}	RM17 5UH	515000	S	N	F	2019-02-27 00:00	E01015960	Thurrock 014A	24939	8	20120	7	24288	8	15055	5	22055	7	19285	6
{85866A64-AC8A-143F-E053-6B04A8C06A15}	IG7 6ND	550000	F	N	L	2019-02-15 00:00	E01021749	Epping Forest 016A	23873	8	21748	7	20143	7	12952	4	28884	9	17201	6
{85866A64-AC8B-143F-E053-6B04A8C06A15}	SS4 1RU	260000	T	N	F	2019-03-01 00:00	E01021954	Rochford 007D	15970	5	16140	5	21245	7	4411	2	19498	6	10295	4
{85866A64-AC8C-143F-E053-6B04A8C06A15}	CM1 6LB	190000	F	N	L	2019-02-11 00:00	E01021620	Chelmsford 004D	24150	8	21386	7	23983	8	18399	6	23518	8	17467	6
{85866A64-AC8D-143F-E053-6B04A8C06A15}	RM16 4TZ	211000	F	N	L	2019-02-21 00:00	E01015938	Thurrock 012F	5389	2	3523	2	4376	2	8404	3	10528	4	6107	2
{85866A64-AC8E-143F-E053-6B04A8C06A15}	SS16 5JS	670000	D	N	F	2019-03-01 00:00	E01021299	Basildon 020E	24395	8	28590	9	23910	8	5364	2	23795	8	18656	6
{85866A64-AC90-143F-E053-6B04A8C06A15}	CM9 5JQ	305000	S	N	F	2019-02-20 00:00	E01021889	Maldon 004A	9591	3	9613	3	7414	3	14158	5	15256	5	5650	2
{85866A64-AC91-143F-E053-6B04A8C06A15}	RM16 2PU	283000	S	N	F	2019-02-08 00:00	E01015964	Thurrock 010B	20425	7	20431	7	18320	6	14298	5	21407	7	14284	5
{85866A64-AC92-143F-E053-6B04A8C06A15}	CM2 7TQ	975000	D	N	F	2019-02-22 00:00	E01021571	Chelmsford 013E	18431	6	21393	7	26117	8	13562	5	30385	10	21493	7
{85866A64-AC93-143F-E053-6B04A8C06A15}	SS14 2DJ	170000	F	N	L	2019-03-11 00:00	E01021319	Basildon 017E	7092	3	7985	3	6467	2	1170	1	15819	5	6015	2
{85866A64-AC95-143F-E053-6B04A8C06A15}	RM15 4BJ	110000	F	N	L	2019-02-08 00:00	E01015921	Thurrock 015A	6684	3	8557	3	13478	5	2597	1	19861	7	7746	3
{85866A64-AC96-143F-E053-6B04A8C06A15}	CM8 2DF	162500	F	N	L	2019-02-25 00:00	E01021416	Braintree 017B	21298	7	22876	7	19474	6	15508	5	11026	4	21087	7
{85866A64-AC97-143F-E053-6B04A8C06A15}	CM1 4NX	195000	F	N	L	2019-02-28 00:00	E01021551	Chelmsford 011A	17311	6	24657	8	23072	8	21609	7	28360	9	16887	6
{85866A64-AC99-143F-E053-6B04A8C06A15}	CM14 4AT	415000	F	N	L	2019-02-14 00:00	E01021439	Brentwood 007C	21446	7	18203	6	22992	8	10794	4	20223	7	23880	8
{85866A64-AC9A-143F-E053-6B04A8C06A15}	CO7 9ES	230000	S	N	F	2019-01-21 00:00	E01021740	Colchester 017E	24360	8	17402	6	21307	7	27450	9	22961	7	18298	6
{85866A64-AC9C-143F-E053-6B04A8C06A15}	SS17 0NX	350000	S	N	F	2019-01-11 00:00	E01015990	Thurrock 003D	12827	4	12448	4	12390	4	13711	5	17344	6	5300	2
{85866A64-AC9D-143F-E053-6B04A8C06A15}	CM1 4JP	350000	T	N	F	2019-02-28 00:00	E01021589	Chelmsford 006C	17947	6	14737	5	15976	5	11049	4	22361	7	15834	5
{85866A64-AC9E-143F-E053-6B04A8C06A15}	CM13 1YL	262000	F	N	L	2019-03-21 00:00	E01021453	Brentwood 005B	29525	9	27437	9	23656	8	18405	6	26326	9	26958	9
{85866A64-AC9F-143F-E053-6B04A8C06A15}	RM16 2NU	444000	S	N	F	2019-02-13 00:00	E01015963	Thurrock 010A	6452	2	4170	2	4057	2	15803	5	13582	5	6572	3
{85866A64-ACA0-143F-E053-6B04A8C06A15}	RM14 1QT	427500	S	N	F	2019-03-20 00:00	E01002253	Havering 019A	32507	10	32081	10	31967	10	28727	9	31592	10	26678	9
{85866A64-ACA1-143F-E053-6B04A8C06A15}	CM15 0NJ	672500	D	N	F	2019-02-05 00:00	E01021441	Brentwood 001A	26638	9	23400	8	18517	6	28143	9	31172	10	15231	5
{85866A64-ACA2-143F-E053-6B04A8C06A15}	CO3 0RY	381000	D	N	F	2019-03-01 00:00	E01021722	Colchester 012E	18862	6	17842	6	17870	6	21746	7	15971	5	16131	5
{85866A64-ACA3-143F-E053-6B04A8C06A15}	SS9 5RY	330000	S	N	F	2019-02-06 00:00	E01015833	Southend-on-Sea 001A	28336	9	25242	8	24389	8	27372	9	21716	7	18613	6
{85866A64-ACA4-143F-E053-6B04A8C06A15}	CM2 6RG	470000	D	N	F	2019-02-08 00:00	E01021546	Chelmsford 008C	23080	8	18273	6	26777	9	21458	7	29324	9	22678	7
{85866A64-ACA5-143F-E053-6B04A8C06A15}	SS14 2SE	280000	T	N	F	2019-02-27 00:00	E01021272	Basildon 012E	10135	4	10602	4	8808	3	6768	3	15873	5	3888	2
{85866A64-ACA6-143F-E053-6B04A8C06A15}	CM20 2LN	167500	F	N	L	2019-03-01 00:00	E01021845	Harlow 002B	11094	4	7771	3	9730	3	15203	5	11665	4	7630	3
{85866A64-AEB1-143F-E053-6B04A8C06A15}	CM9 6EW	315000	S	N	F	2019-02-11 00:00	E01021898	Maldon 005F	18168	6	14295	5	10785	4	27929	9	16730	6	12245	4
{85866A64-AEB2-143F-E053-6B04A8C06A15}	CM9 4PT	305000	T	N	F	2019-02-01 00:00	E01021887	Maldon 003D	23350	8	23869	8	21322	7	28248	9	27271	9	16625	6
{85866A64-AEB3-143F-E053-6B04A8C06A15}	EN9 3XP	295000	F	N	L	2019-03-25 00:00	E01021817	Epping Forest 008E	12905	4	13646	5	14617	5	10480	4	23275	8	7501	3
{85866A64-AEB4-143F-E053-6B04A8C06A15}	SS8 7DF	270000	D	N	F	2019-01-25 00:00	E01021500	Castle Point 012E	1311	1	717	1	339	1	5606	2	4480	2	4559	2
{85866A64-AEB5-143F-E053-6B04A8C06A15}	RM16 3HD	327000	S	N	F	2019-03-04 00:00	E01015977	Thurrock 004A	22346	7	26613	9	21663	7	8007	3	27627	9	14784	5
{85866A64-AEB6-143F-E053-6B04A8C06A15}	SS7 3LA	400000	D	N	F	2019-02-25 00:00	E01021510	Castle Point 002B	22348	7	20969	7	19176	6	30215	10	15534	5	14229	5
{85866A64-AEB7-143F-E053-6B04A8C06A15}	CO15 4RN	265000	D	N	F	2019-02-28 00:00	E01021984	Tendring 010A	11388	4	11680	4	8116	3	24500	8	7724	3	5645	2
{85866A64-AEB8-143F-E053-6B04A8C06A15}	CO5 9TL	475000	D	N	F	2019-02-22 00:00	E01021643	Colchester 019A	27601	9	28946	9	30451	10	22211	7	28914	9	17286	6
{85866A64-AEB9-143F-E053-6B04A8C06A15}	CO1 2TR	148000	T	N	F	2019-02-25 00:00	E01021648	Colchester 007C	11046	4	12456	4	12942	4	1984	1	12984	4	23468	8
{85866A64-AEBA-143F-E053-6B04A8C06A15}	SS8 7EN	188000	D	N	F	2019-03-08 00:00	E01021497	Castle Point 012D	14538	5	13598	5	15491	5	21146	7	18078	6	3213	1
{85866A64-AEBC-143F-E053-6B04A8C06A15}	CO7 9EX	210000	S	N	F	2019-03-21 00:00	E01021737	Colchester 017B	22925	7	22881	7	22398	7	31210	10	18304	6	20513	7
{85866A64-AEBE-143F-E053-6B04A8C06A15}	RM16 4DS	315000	S	N	F	2019-01-25 00:00	E01015950	Thurrock 013D	17120	6	17211	6	19001	6	12625	4	22196	7	11428	4
{85866A64-AEC2-143F-E053-6B04A8C06A15}	CO9 3LH	350000	S	N	F	2019-03-01 00:00	E01021400	Braintree 003D	24365	8	21658	7	21328	7	27672	9	27982	9	14017	5
{85866A64-AEC3-143F-E053-6B04A8C06A15}	SS3 9WD	420000	S	N	F	2019-03-01 00:00	E01015877	Southend-on-Sea 013B	8613	3	5923	2	6794	3	11915	4	10273	4	6874	3
{85866A64-AEC4-143F-E053-6B04A8C06A15}	SS9 1DE	250000	F	N	L	2019-02-08 00:00	E01015846	Southend-on-Sea 011B	30087	10	25636	8	27931	9	19177	6	29251	9	26669	9
{85866A64-AEC5-143F-E053-6B04A8C06A15}	CM14 4NB	607500	S	N	F	2019-02-07 00:00	E01021438	Brentwood 006A	31559	10	31890	10	31808	10	26150	8	32488	10	27709	9
{85866A64-AEC6-143F-E053-6B04A8C06A15}	CM9 4PX	288000	T	N	F	2019-02-15 00:00	E01021887	Maldon 003D	23350	8	23869	8	21322	7	28248	9	27271	9	16625	6
{85866A64-AEC7-143F-E053-6B04A8C06A15}	CM16 4FE	300000	F	N	L	2019-02-11 00:00	E01021757	Epping Forest 006B	29787	10	28672	9	30757	10	10426	4	31544	10	29333	9
{85866A64-AEC8-143F-E053-6B04A8C06A15}	RM15 5LR	300000	T	N	F	2019-02-22 00:00	E01015972	Thurrock 006C	13691	5	11041	4	14807	5	9180	3	16249	5	9448	3
{85866A64-AEC9-143F-E053-6B04A8C06A15}	CO12 4WL	176000	D	N	F	2019-02-28 00:00	E01022004	Tendring 004D	14048	5	15068	5	14549	5	11392	4	6122	2	8064	3
{85866A64-AECA-143F-E053-6B04A8C06A15}	SS5 6HG	290000	S	N	F	2019-02-08 00:00	E01021944	Rochford 001C	27306	9	28072	9	25457	8	20737	7	31033	10	9861	4
{85866A64-AECB-143F-E053-6B04A8C06A15}	CM9 4NR	323500	S	N	F	2019-02-08 00:00	E01021886	Maldon 003C	23349	8	21830	7	17080	6	28749	9	24086	8	15697	5
{85866A64-AECC-143F-E053-6B04A8C06A15}	CM8 1TZ	225000	T	N	F	2019-02-11 00:00	E01021427	Braintree 016C	10404	4	11664	4	11053	4	9413	3	12465	4	5187	2
{85866A64-AECD-143F-E053-6B04A8C06A15}	SS1 2SY	450000	S	N	F	2019-02-11 00:00	E01015892	Southend-on-Sea 016D	28552	9	24107	8	26125	8	18595	6	27022	9	19373	6
{85866A64-AECE-143F-E053-6B04A8C06A15}	IG1 2UW	375000	T	N	F	2019-03-08 00:00	E01003739	Redbridge 031C	14512	5	8555	3	15658	5	9756	3	25908	8	22039	7
{85866A64-AECF-143F-E053-6B04A8C06A15}	RM16 6AP	210000	F	N	L	2019-02-15 00:00	E01033613	Thurrock 019D	29837	10	30295	10	30798	10	23593	8	29863	10	24058	8
{85866A64-AED0-143F-E053-6B04A8C06A15}	CO1 2PF	318000	D	N	F	2019-02-01 00:00	E01021648	Colchester 007C	11046	4	12456	4	12942	4	1984	1	12984	4	23468	8
{85866A64-AED1-143F-E053-6B04A8C06A15}	CO12 5FG	255000	D	N	F	2019-03-13 00:00	E01022002	Tendring 004C	16473	6	15310	5	12675	4	26099	8	11942	4	9408	3
{85866A64-AED2-143F-E053-6B04A8C06A15}	SS7 3AD	312500	S	N	F	2019-02-15 00:00	E01021512	Castle Point 004D	28781	9	27306	9	27752	9	27897	9	27508	9	14976	5
{85866A64-AED3-143F-E053-6B04A8C06A15}	CO15 6PY	58000	F	N	L	2019-01-24 00:00	E01022027	Tendring 016D	1294	1	3683	2	1076	1	598	1	1515	1	4282	2
{85866A64-AED4-143F-E053-6B04A8C06A15}	CM20 2PN	334500	S	N	F	2019-03-08 00:00	E01021853	Harlow 003E	12925	4	14216	5	14571	5	4608	2	15773	5	10573	4
{85866A64-AA55-143F-E053-6B04A8C06A15}	SS15 6QR	385000	D	N	F	2019-02-18 00:00	E01021275	Basildon 014B	17300	6	18736	6	12667	4	9199	3	19596	6	11949	4
{85866A64-AA56-143F-E053-6B04A8C06A15}	CO2 8BS	278000	S	N	F	2019-03-21 00:00	E01021664	Colchester 016C	14329	5	16323	5	15897	5	14863	5	16310	5	13043	4
{85866A64-AA57-143F-E053-6B04A8C06A15}	SS9 1QA	475000	S	N	F	2019-03-01 00:00	E01015847	Southend-on-Sea 011C	23770	8	19789	7	20554	7	17068	6	24753	8	21293	7
{85866A64-AA59-143F-E053-6B04A8C06A15}	RM1 4EF	600000	T	N	F	2019-03-07 00:00	E01002339	Havering 008D	29691	10	29664	10	30230	10	19751	7	30293	10	20315	7
{85866A64-AA5A-143F-E053-6B04A8C06A15}	EN9 1TA	340000	T	N	F	2019-02-15 00:00	E01021808	Epping Forest 008B	12226	4	10077	4	14236	5	16316	5	22428	7	5108	2
{85866A64-AA5B-143F-E053-6B04A8C06A15}	IG10 3DE	455000	T	N	F	2019-03-01 00:00	E01021785	Epping Forest 014D	14744	5	11692	4	12526	4	10792	4	20278	7	9065	3
{85866A64-AA5C-143F-E053-6B04A8C06A15}	RM15 6EB	347500	S	N	F	2019-02-14 00:00	E01015930	Thurrock 007D	12172	4	13319	5	14322	5	9226	3	21746	7	7972	3
{85866A64-AA5D-143F-E053-6B04A8C06A15}	CM18 7BJ	413000	D	N	F	2019-02-19 00:00	E01021823	Harlow 006D	6901	3	5765	2	6141	2	10620	4	7576	3	3880	2
{85866A64-AA5E-143F-E053-6B04A8C06A15}	SS2 6XJ	288000	S	N	F	2019-03-08 00:00	E01015865	Southend-on-Sea 002C	15188	5	16044	5	14365	5	21553	7	16035	5	6796	3
{85866A64-AA5F-143F-E053-6B04A8C06A15}	SS17 9AD	525000	D	N	F	2019-02-14 00:00	E01015943	Thurrock 001A	20575	7	23382	8	23197	8	14259	5	26304	9	11565	4
{85866A64-AA60-143F-E053-6B04A8C06A15}	IG7 5BX	635000	T	N	F	2019-03-01 00:00	E01021752	Epping Forest 016D	23975	8	22798	7	29130	9	10134	4	30647	10	18023	6
{85866A64-AA62-143F-E053-6B04A8C06A15}	IG10 3LP	300000	T	N	F	2019-02-18 00:00	E01021771	Epping Forest 013A	5221	2	4339	2	5344	2	7090	3	12147	4	3244	1
{85866A64-AA63-143F-E053-6B04A8C06A15}	SS9 3EB	425000	D	N	F	2019-03-18 00:00	E01015821	Southend-on-Sea 005B	20310	7	17351	6	16442	6	18209	6	17519	6	16759	6
{85866A64-AA64-143F-E053-6B04A8C06A15}	SS16 4BE	265000	T	N	F	2019-02-15 00:00	E01021295	Basildon 020B	9576	3	9463	3	11000	4	2142	1	16504	6	6803	3
{85866A64-AA65-143F-E053-6B04A8C06A15}	E4 9SG	630000	S	N	F	2019-03-06 00:00	E01004386	Waltham Forest 003C	25868	8	27219	9	24801	8	17798	6	25645	8	22079	7
{85866A64-AA66-143F-E053-6B04A8C06A15}	CM11 2BZ	435000	S	N	F	2019-02-21 00:00	E01021244	Basildon 004A	31412	10	30900	10	31642	10	17370	6	30269	10	28755	9
{85866A64-AA67-143F-E053-6B04A8C06A15}	SS17 0RE	338000	S	N	F	2019-03-15 00:00	E01015950	Thurrock 013D	17120	6	17211	6	19001	6	12625	4	22196	7	11428	4
{85866A64-AA68-143F-E053-6B04A8C06A15}	IG6 2UT	445000	T	N	F	2019-03-12 00:00	E01003702	Redbridge 006E	17235	6	14595	5	19884	7	10579	4	23633	8	17649	6
{85866A64-AA69-143F-E053-6B04A8C06A15}	SS3 9DX	220000	T	N	F	2019-03-13 00:00	E01015917	Southend-on-Sea 017D	3667	2	3614	2	3062	1	5121	2	6131	2	1923	1
{85866A64-AA6A-143F-E053-6B04A8C06A15}	SS13 3DH	470000	D	N	F	2019-03-11 00:00	E01021310	Basildon 022B	11590	4	16381	5	16347	5	961	1	16266	5	9371	3
{85866A64-AA6B-143F-E053-6B04A8C06A15}	SS16 5HU	422000	S	N	F	2019-02-28 00:00	E01021299	Basildon 020E	24395	8	28590	9	23910	8	5364	2	23795	8	18656	6
{85866A64-AA6C-143F-E053-6B04A8C06A15}	CB11 3QR	277000	T	N	F	2019-03-01 00:00	E01022073	Uttlesford 003D	29380	9	25334	8	27979	9	20515	7	26932	9	20222	7
{85866A64-AA6D-143F-E053-6B04A8C06A15}	SS3 8AH	311500	D	N	F	2019-03-04 00:00	E01015915	Southend-on-Sea 017B	24412	8	26015	8	25772	8	8167	3	20177	7	21633	7
{85866A64-AA6E-143F-E053-6B04A8C06A15}	SS16 5DU	123000	T	N	F	2019-03-01 00:00	E01021296	Basildon 020C	12969	4	12018	4	11559	4	3827	2	19569	6	11857	4
{85866A64-AA6F-143F-E053-6B04A8C06A15}	CM12 0AR	867000	D	N	F	2019-02-12 00:00	E01021247	Basildon 003E	31165	10	27843	9	29719	10	23462	8	28815	9	26921	9
{85866A64-AA70-143F-E053-6B04A8C06A15}	CM2 6RT	475000	D	N	F	2019-02-28 00:00	E01021548	Chelmsford 013A	29046	9	25713	8	27049	9	22822	7	30525	10	24905	8
{85866A64-AA71-143F-E053-6B04A8C06A15}	EN9 1LE	430000	S	N	F	2019-02-28 00:00	E01021813	Epping Forest 007B	24014	8	27320	9	26380	9	10253	4	27608	9	10840	4
{85866A64-AA72-143F-E053-6B04A8C06A15}	CO6 3LJ	255000	T	N	F	2019-03-08 00:00	E01021729	Colchester 003C	24483	8	19484	6	15744	5	29791	10	19873	7	23768	8
{85866A64-AA73-143F-E053-6B04A8C06A15}	CM3 5TT	290000	S	N	F	2019-03-18 00:00	E01021611	Chelmsford 019A	29960	10	29487	9	27772	9	27886	9	31237	10	19667	6
{85866A64-AA74-143F-E053-6B04A8C06A15}	RM20 3JT	186500	F	N	L	2019-02-25 00:00	E01016012	Thurrock 015C	10896	4	12837	4	17782	6	4963	2	17870	6	10767	4
{85866A64-AA75-143F-E053-6B04A8C06A15}	CM1 6YS	320000	S	N	F	2019-02-08 00:00	E01021621	Chelmsford 007B	23198	8	23852	8	26567	9	15829	5	30199	10	15917	5
{85866A64-AA76-143F-E053-6B04A8C06A15}	SS3 8AF	455000	D	N	F	2019-03-15 00:00	E01015915	Southend-on-Sea 017B	24412	8	26015	8	25772	8	8167	3	20177	7	21633	7
{85866A64-AA77-143F-E053-6B04A8C06A15}	IG7 5LR	290000	F	N	L	2019-03-15 00:00	E01021766	Epping Forest 017C	26195	8	24488	8	29626	10	6783	3	30679	10	23618	8
{85866A64-AA78-143F-E053-6B04A8C06A15}	RM17 6BH	315000	T	N	F	2019-03-01 00:00	E01015967	Thurrock 014B	22370	7	21402	7	22563	7	15374	5	25199	8	15398	5
{85866A64-ACA7-143F-E053-6B04A8C06A15}	CO6 1TN	138000	F	N	L	2019-02-21 00:00	E01021377	Braintree 014A	23647	8	20705	7	18820	6	27648	9	26115	8	14542	5
{85866A64-ACA9-143F-E053-6B04A8C06A15}	CO3 3AZ	465000	S	N	F	2019-02-08 00:00	E01021653	Colchester 013C	32188	10	31314	10	30533	10	30257	10	27899	9	32057	10
{85866A64-ACAA-143F-E053-6B04A8C06A15}	SS7 5HJ	340000	S	N	F	2019-02-22 00:00	E01021524	Castle Point 007E	23277	8	19283	6	19957	7	15394	5	22022	7	14430	5
{85866A64-ACAB-143F-E053-6B04A8C06A15}	CO15 2RQ	150000	D	N	F	2019-02-01 00:00	E01021990	Tendring 018C	1514	1	1637	1	1100	1	6831	3	1626	1	595	1
{85866A64-ACAC-143F-E053-6B04A8C06A15}	CO2 7RU	212500	T	N	F	2019-03-08 00:00	E01021684	Colchester 011B	23032	8	17507	6	22837	7	17107	6	20487	7	22699	7
{85866A64-ACAD-143F-E053-6B04A8C06A15}	CM2 9QX	298000	T	N	F	2019-03-20 00:00	E01021563	Chelmsford 014B	11098	4	10378	4	7605	3	10686	4	13558	5	13871	5
{8CAC1318-B9FC-0253-E053-6B04A8C08E51}	S2 1WY	110000	T	N	F	2019-06-10 00:00	E01008015	Sheffield 039D	1162	1	2225	1	777	1	5453	2	1271	1	319	1
{8CAC1318-B9FD-0253-E053-6B04A8C08E51}	S11 8AA	164000	F	N	L	2019-04-12 00:00	E01008109	Sheffield 042B	7254	3	6974	3	11841	4	3822	2	7524	3	9593	3
{8CAC1318-B9FE-0253-E053-6B04A8C08E51}	DN3 1FE	148500	S	N	F	2019-05-21 00:00	E01007624	Doncaster 007D	28636	9	26447	9	24791	8	17650	6	23198	8	22191	7
{8CAC1318-B9FF-0253-E053-6B04A8C08E51}	S66 3RY	210000	D	N	F	2019-05-28 00:00	E01032927	Rotherham 012F	13877	5	15947	5	11078	4	8977	3	6644	3	17831	6
{8CAC1318-BA00-0253-E053-6B04A8C08E51}	S72 8WP	100000	S	N	F	2019-05-24 00:00	E01007331	Barnsley 003B	12603	4	13051	4	9288	3	7928	3	8500	3	9788	3
{8CAC1318-BA01-0253-E053-6B04A8C08E51}	S9 4PR	105000	T	N	L	2019-05-22 00:00	E01007907	Sheffield 032A	9719	3	7658	3	10031	4	16490	6	12400	4	5428	2
{8CAC1318-BA02-0253-E053-6B04A8C08E51}	S13 7DP	64000	F	N	L	2019-06-10 00:00	E01007970	Sheffield 049D	270	1	666	1	30	1	317	1	23	1	2506	1
{8CAC1318-BA03-0253-E053-6B04A8C08E51}	S73 0DH	66000	F	N	L	2019-03-15 00:00	E01032925	Barnsley 026G	9285	3	10883	4	10686	4	14007	5	1648	1	5891	2
{8CAC1318-BA04-0253-E053-6B04A8C08E51}	DN5 0RE	75000	T	N	F	2019-06-12 00:00	E01007511	Doncaster 010E	2201	1	1684	1	2923	1	1436	1	4410	2	874	1
{8CAC1318-BA05-0253-E053-6B04A8C08E51}	S1 4EY	135000	F	N	L	2019-05-17 00:00	E01033265	Sheffield 074C	10947	4	24154	8	21735	7	698	1	8259	3	22355	7
{8CAC1318-BA06-0253-E053-6B04A8C08E51}	DN4 7DQ	92500	F	N	L	2019-01-25 00:00	E01007527	Doncaster 027B	23327	8	25883	8	24165	8	12315	4	17405	6	26914	9
{8CAC1318-BA07-0253-E053-6B04A8C08E51}	DN5 0EN	120000	S	N	F	2019-04-29 00:00	E01007508	Doncaster 010B	1508	1	1623	1	1786	1	451	1	4540	2	524	1
{8CAC1318-BA08-0253-E053-6B04A8C08E51}	S70 6AX	130000	S	N	F	2019-05-31 00:00	E01007415	Barnsley 013C	7917	3	9785	3	7267	3	1395	1	4999	2	12003	4
{8CAC1318-BA09-0253-E053-6B04A8C08E51}	S11 9PR	367000	T	N	L	2019-04-25 00:00	E01007928	Sheffield 055B	32441	10	31687	10	30841	10	28498	9	28998	9	32561	10
{8CAC1318-BA0A-0253-E053-6B04A8C08E51}	S6 3RR	194000	S	N	F	2019-06-06 00:00	E01008155	Sheffield 024D	14859	5	12510	4	15996	5	16351	5	12525	4	10800	4
{8CAC1318-BA0B-0253-E053-6B04A8C08E51}	S26 5QR	185000	T	N	F	2019-06-11 00:00	E01007751	Rotherham 033C	14770	5	14155	5	13200	5	8654	3	9243	3	14474	5
{8CAC1318-BA0C-0253-E053-6B04A8C08E51}	DN9 3PL	173000	S	N	F	2019-06-14 00:00	E01007599	Doncaster 026A	23888	8	25776	8	21441	7	17061	6	18899	6	20689	7
{8CAC1318-BA0D-0253-E053-6B04A8C08E51}	S11 9SF	525000	S	N	L	2019-05-31 00:00	E01007928	Sheffield 055B	32441	10	31687	10	30841	10	28498	9	28998	9	32561	10
{8CAC1318-BA0E-0253-E053-6B04A8C08E51}	S6 4QB	157000	S	N	F	2019-05-31 00:00	E01007992	Sheffield 021B	21154	7	22066	7	21428	7	17295	6	11244	4	24459	8
{8CAC1318-BA0F-0253-E053-6B04A8C08E51}	S64 9NA	38000	T	N	F	2019-05-31 00:00	E01007577	Doncaster 031F	249	1	883	1	482	1	520	1	312	1	202	1
{8CAC1318-BA10-0253-E053-6B04A8C08E51}	S2 3HG	157000	T	N	F	2019-05-17 00:00	E01008101	Sheffield 043D	3673	2	3996	2	2831	1	4826	2	2277	1	5467	2
{8CAC1318-BA11-0253-E053-6B04A8C08E51}	S35 2EP	172500	S	N	F	2019-04-30 00:00	E01007890	Sheffield 004C	25917	8	27762	9	24592	8	16163	5	16679	6	19287	6
{8CAC1318-BA12-0253-E053-6B04A8C08E51}	S72 7LJ	105000	S	N	F	2019-05-22 00:00	E01007332	Barnsley 006C	2908	1	5847	2	3972	2	1931	1	414	1	1199	1
{8CAC1318-BA13-0253-E053-6B04A8C08E51}	S10 1FG	180000	T	N	L	2019-06-18 00:00	E01007962	Sheffield 029C	19368	6	17242	6	19736	7	24797	8	6459	2	24004	8
{8CAC1318-BA15-0253-E053-6B04A8C08E51}	S8 0SU	138000	F	N	L	2019-05-03 00:00	E01007829	Sheffield 059B	18870	6	19466	6	17093	6	11672	4	15393	5	23050	8
{8CAC1318-BA17-0253-E053-6B04A8C08E51}	S62 6FL	158000	S	N	F	2019-06-19 00:00	E01007776	Rotherham 008B	7127	3	6142	2	6502	2	3723	2	5748	2	8077	3
{8CAC1318-BA18-0253-E053-6B04A8C08E51}	S74 0LU	159000	T	N	F	2019-06-17 00:00	E01007457	Barnsley 029E	6545	2	7910	3	5813	2	5125	2	2107	1	5878	2
{8CAC1318-BA19-0253-E053-6B04A8C08E51}	DN3 2FR	145000	S	N	F	2019-05-24 00:00	E01033259	Doncaster 014E	21123	7	21162	7	24460	8	11922	4	9475	3	18778	6
{8CAC1318-BA1A-0253-E053-6B04A8C08E51}	S36 9QS	300000	D	N	F	2019-06-17 00:00	E01007427	Barnsley 024A	21458	7	18937	6	16294	5	27173	9	16746	6	17864	6
{8CAC1318-BA1C-0253-E053-6B04A8C08E51}	S73 9HN	168000	S	N	F	2019-05-31 00:00	E01007351	Barnsley 020D	6896	3	9374	3	7348	3	2241	1	5363	2	3471	2
{8CAC1318-BC26-0253-E053-6B04A8C08E51}	S75 1FE	209950	D	Y	F	2019-05-17 00:00	E01007381	Barnsley 012C	23905	8	22968	7	17514	6	23470	8	11876	4	22177	7
{8CAC1318-BC27-0253-E053-6B04A8C08E51}	DN2 5SS	105000	S	N	F	2019-05-31 00:00	E01007650	Doncaster 015B	10921	4	12610	4	8547	3	8575	3	5628	2	10177	4
{8CAC1318-BC28-0253-E053-6B04A8C08E51}	S74 9LS	115000	S	N	F	2019-01-18 00:00	E01007388	Barnsley 029A	16032	5	17787	6	12434	4	11469	4	7756	3	15568	5
{8CAC1318-BC29-0253-E053-6B04A8C08E51}	DN6 0BF	109995	T	Y	F	2019-04-30 00:00	E01007489	Doncaster 002C	12952	4	11649	4	13976	5	15128	5	8240	3	7818	3
{8CAC1318-BC2A-0253-E053-6B04A8C08E51}	S71 4GG	219995	D	Y	F	2019-05-24 00:00	E01007439	Barnsley 001D	20520	7	21928	7	15440	5	6266	2	17567	6	17401	6
{8CAC1318-BC2C-0253-E053-6B04A8C08E51}	S2 4DD	68750	F	Y	L	2019-05-22 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC2D-0253-E053-6B04A8C08E51}	S8 8NA	217000	S	Y	F	2019-05-30 00:00	E01007827	Sheffield 064A	22051	7	25854	8	21430	7	7499	3	15185	5	24825	8
{8CAC1318-BC2E-0253-E053-6B04A8C08E51}	DN4 5EU	75000	T	N	F	2019-05-17 00:00	E01007644	Doncaster 019A	13814	5	16416	5	14453	5	3889	2	14541	5	10337	4
{8CAC1318-BC2F-0253-E053-6B04A8C08E51}	S2 4DD	75750	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC30-0253-E053-6B04A8C08E51}	S10 2LW	300000	F	Y	L	2019-05-16 00:00	E01008104	Sheffield 036E	18528	6	17417	6	24903	8	13247	5	14188	5	18949	6
{8CAC1318-BC31-0253-E053-6B04A8C08E51}	DN6 7FJ	129995	S	Y	F	2019-05-30 00:00	E01007466	Doncaster 009C	1164	1	1506	1	1436	1	322	1	3279	1	308	1
{8CAC1318-BC32-0253-E053-6B04A8C08E51}	S2 4DD	68500	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC33-0253-E053-6B04A8C08E51}	S2 4DD	72500	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC35-0253-E053-6B04A8C08E51}	S2 4DD	72500	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC36-0253-E053-6B04A8C08E51}	S2 4DD	72500	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC37-0253-E053-6B04A8C08E51}	S2 4DD	66500	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC38-0253-E053-6B04A8C08E51}	S2 4DD	71750	F	Y	L	2019-05-11 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC39-0253-E053-6B04A8C08E51}	S2 4DD	66500	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC3A-0253-E053-6B04A8C08E51}	S2 4DD	66500	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC3B-0253-E053-6B04A8C08E51}	S2 4FS	69750	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC3C-0253-E053-6B04A8C08E51}	S2 4DD	67750	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC3D-0253-E053-6B04A8C08E51}	S2 4DD	67750	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC3E-0253-E053-6B04A8C08E51}	S2 4DD	67500	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC3F-0253-E053-6B04A8C08E51}	S2 4DD	71750	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC40-0253-E053-6B04A8C08E51}	S2 4DD	65500	F	Y	L	2019-05-11 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC41-0253-E053-6B04A8C08E51}	S2 4DD	65500	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC42-0253-E053-6B04A8C08E51}	S2 4DD	73750	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC43-0253-E053-6B04A8C08E51}	S2 4DD	75750	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BC44-0253-E053-6B04A8C08E51}	S2 4DD	71750	F	Y	L	2019-05-20 00:00	E01033273	Sheffield 042F	12083	4	19521	6	28255	9	6888	3	9767	3	4021	2
{8CAC1318-BE39-0253-E053-6B04A8C08E51}	SW12 0DT	450000	F	N	L	2019-06-14 00:00	E01004473	Wandsworth 026A	22310	7	19712	7	24163	8	14189	5	17465	6	32655	10
{8CAC1318-BE3B-0253-E053-6B04A8C08E51}	SW16 2RJ	300000	F	N	L	2019-05-31 00:00	E01003154	Lambeth 030E	8914	3	6554	2	7553	3	15102	5	9763	3	18743	6
{8CAC1318-BE3C-0253-E053-6B04A8C08E51}	SW12 9DS	437000	F	N	L	2019-05-31 00:00	E01004474	Wandsworth 021B	16534	6	15734	5	21772	7	7773	3	17721	6	22958	7
{8CAC1318-BE3D-0253-E053-6B04A8C08E51}	SE18 6TJ	452000	F	N	L	2019-06-11 00:00	E01033736	Greenwich 004H	23883	8	32496	10	32745	10	7444	3	20960	7	24563	8
{8CAC1318-BE3E-0253-E053-6B04A8C08E51}	SW12 9PL	499999	F	N	L	2019-05-31 00:00	E01004473	Wandsworth 026A	22310	7	19712	7	24163	8	14189	5	17465	6	32655	10
{8CAC1318-BE3F-0253-E053-6B04A8C08E51}	SE18 3AT	220000	F	N	L	2019-05-31 00:00	E01001700	Greenwich 011D	7478	3	6462	2	10226	4	8491	3	11202	4	12202	4
{8CAC1318-BE40-0253-E053-6B04A8C08E51}	SW12 0NU	370000	F	N	L	2019-06-14 00:00	E01003156	Lambeth 023B	15573	5	15120	5	17502	6	17108	6	9305	3	31009	10
{8CAC1318-BE41-0253-E053-6B04A8C08E51}	SE5 0XH	370000	F	N	L	2019-06-21 00:00	E01003926	Southwark 021F	7330	3	5254	2	10527	4	6929	3	10582	4	18955	6
{8CAC1318-BE42-0253-E053-6B04A8C08E51}	SE28 0NE	425000	T	N	F	2019-06-07 00:00	E01033740	Greenwich 002F	14071	5	10245	4	15436	5	7524	3	20561	7	26399	9
{8CAC1318-BE44-0253-E053-6B04A8C08E51}	SW16 5BY	405000	F	N	L	2019-04-29 00:00	E01003145	Lambeth 034D	11635	4	15110	5	19155	6	7931	3	16040	5	21267	7
{8CAC1318-BE45-0253-E053-6B04A8C08E51}	SE4 1HS	470000	F	N	F	2019-04-23 00:00	E01003275	Lewisham 014C	7727	3	5081	2	7066	3	21449	7	10199	4	16583	6
{8CAC1318-BE46-0253-E053-6B04A8C08E51}	SE15 6HR	260000	F	N	L	2019-04-12 00:00	E01004012	Southwark 019C	9413	3	6942	3	10569	4	13684	5	15887	5	21252	7
{8CAC1318-BE47-0253-E053-6B04A8C08E51}	SE17 2RB	310000	F	N	L	2019-06-07 00:00	E01003964	Southwark 015A	5759	2	7268	3	8021	3	1587	1	15704	5	15091	5
{8CAC1318-BE48-0253-E053-6B04A8C08E51}	SE18 6JG	200000	F	N	L	2019-04-25 00:00	E01033735	Greenwich 004G	9152	3	11023	4	18556	6	2385	1	10493	4	20804	7
{8CAC1318-BE49-0253-E053-6B04A8C08E51}	SE22 8BZ	353000	F	N	L	2019-05-20 00:00	E01004045	Southwark 027A	9397	3	5685	2	7497	3	24340	8	14852	5	18230	6
{8CAC1318-BE4A-0253-E053-6B04A8C08E51}	SE5 7GD	190000	F	N	L	2019-06-06 00:00	E01003916	Southwark 020B	10919	4	9217	3	15610	5	8197	3	15830	5	24176	8
{8CAC1318-BE4C-0253-E053-6B04A8C08E51}	TW1 4NF	652000	T	N	F	2019-06-20 00:00	E01003884	Richmond upon Thames 016C	29942	10	27722	9	27198	9	15378	5	31317	10	32604	10
{8CAC1318-BE4D-0253-E053-6B04A8C08E51}	SE19 1LS	397500	F	N	L	2019-05-24 00:00	E01003948	Southwark 033D	16743	6	16049	5	18666	6	7249	3	18374	6	31477	10
{8CAC1318-BE4E-0253-E053-6B04A8C08E51}	SE28 0GJ	241000	F	N	L	2019-06-06 00:00	E01033742	Greenwich 007F	20945	7	19844	7	27920	9	19491	6	22041	7	24139	8
{8CAC1318-BE4F-0253-E053-6B04A8C08E51}	SW15 2SR	440000	F	N	L	2019-05-31 00:00	E01004507	Wandsworth 014E	26239	8	22845	7	30249	10	26781	9	30369	10	27933	9
{8CAC1318-BE50-0253-E053-6B04A8C08E51}	SE1 3BP	700000	F	N	L	2019-05-29 00:00	E01032803	Southwark 003J	17880	6	18347	6	28160	9	17793	6	11084	4	30293	10
{8CAC1318-BE51-0253-E053-6B04A8C08E51}	SE12 8JP	375000	F	N	L	2019-06-07 00:00	E01001658	Greenwich 034C	15955	5	12696	4	18519	6	14592	5	23354	8	22262	7
{8CAC1318-BE52-0253-E053-6B04A8C08E51}	SE9 3NZ	350000	T	N	F	2019-04-10 00:00	E01001596	Greenwich 032A	25312	8	24812	8	23260	8	20000	7	24571	8	19475	6
{8CAC1318-BE53-0253-E053-6B04A8C08E51}	SE2 9NU	230000	F	N	L	2019-06-14 00:00	E01001578	Greenwich 003D	9697	3	7328	3	10349	4	6101	2	18493	6	13609	5
{8CAC1318-BE54-0253-E053-6B04A8C08E51}	TW12 1DW	615000	S	N	F	2019-05-08 00:00	E01003813	Richmond upon Thames 019B	30765	10	30944	10	26966	9	22208	7	31051	10	32705	10
{8CAC1318-BE56-0253-E053-6B04A8C08E51}	TW2 5BE	459950	F	N	L	2019-06-17 00:00	E01003898	Richmond upon Thames 015A	27203	9	22641	7	27077	9	16846	6	28787	9	32000	10
{8CAC1318-BE57-0253-E053-6B04A8C08E51}	SE22 8QP	875000	T	N	F	2019-06-20 00:00	E01004072	Southwark 030E	25533	8	26019	8	26939	9	12498	4	28838	9	31643	10
{8CAC1318-BE58-0253-E053-6B04A8C08E51}	SE28 0LU	255000	F	N	L	2019-05-10 00:00	E01033739	Greenwich 002E	15162	5	11720	4	21087	7	18894	6	19522	6	25501	8
{8CAC1318-BE59-0253-E053-6B04A8C08E51}	SE18 5EL	200000	F	N	L	2019-05-29 00:00	E01001710	Greenwich 005D	6464	2	3640	2	4850	2	16633	6	10463	4	9849	3
{8CAC1318-C051-0253-E053-6B04A8C08E51}	SE3 0TG	487350	F	N	L	2019-06-05 00:00	E01003200	Lewisham 009B	22667	7	27917	9	31167	10	7037	3	27269	9	31772	10
{8CAC1318-C052-0253-E053-6B04A8C08E51}	E16 2SG	519000	F	N	L	2019-04-26 00:00	E01033577	Newham 037E	15262	5	14172	5	22784	7	19262	6	21403	7	19376	6
{8CAC1318-C054-0253-E053-6B04A8C08E51}	SW17 8AU	700000	F	N	L	2019-05-07 00:00	E01004481	Wandsworth 029A	18761	6	17594	6	21179	7	11613	4	17340	6	31137	10
{8CAC1318-C055-0253-E053-6B04A8C08E51}	E16 2PT	714000	F	N	L	2019-05-24 00:00	E01033577	Newham 037E	15262	5	14172	5	22784	7	19262	6	21403	7	19376	6
{8CAC1318-C056-0253-E053-6B04A8C08E51}	E16 2JW	499000	F	N	L	2019-06-07 00:00	E01033577	Newham 037E	15262	5	14172	5	22784	7	19262	6	21403	7	19376	6
{8CAC1318-C057-0253-E053-6B04A8C08E51}	SE22 9EA	485000	F	N	L	2019-04-26 00:00	E01003955	Southwark 028B	15889	5	15398	5	14737	5	16291	5	11223	4	27367	9
{8A78B2B0-1D2B-5CB0-E053-6B04A8C0F504}	NE38 8HN	80000	T	N	F	2019-05-03 00:00	E01008847	Sunderland 017C	3112	1	2660	1	2747	1	17269	6	1907	1	1682	1
{8A78B2B0-1D2C-5CB0-E053-6B04A8C0F504}	NE39 2LH	88000	T	N	F	2019-03-22 00:00	E01008183	Gateshead 024A	7454	3	7102	3	7266	3	4059	2	5275	2	8249	3
{8A78B2B0-1D2D-5CB0-E053-6B04A8C0F504}	NE11 9FG	75500	F	N	L	2019-02-08 00:00	E01008209	Gateshead 007A	10554	4	8846	3	8960	3	22247	7	2817	1	11829	4
{8A78B2B0-1D2E-5CB0-E053-6B04A8C0F504}	NE28 7JP	92500	F	N	L	2019-03-29 00:00	E01008576	North Tyneside 029D	6765	3	4703	2	5817	2	11003	4	6336	2	8792	3
{8A78B2B0-1D2F-5CB0-E053-6B04A8C0F504}	NE29 7AE	72000	F	N	L	2019-04-29 00:00	E01008484	North Tyneside 023C	2439	1	1829	1	1437	1	8523	3	2768	1	2560	1
{8A78B2B0-1D30-5CB0-E053-6B04A8C0F504}	NE29 7AH	50000	F	N	L	2019-05-10 00:00	E01008484	North Tyneside 023C	2439	1	1829	1	1437	1	8523	3	2768	1	2560	1
{8A78B2B0-1D32-5CB0-E053-6B04A8C0F504}	DH4 6HX	61500	S	N	F	2019-05-07 00:00	E01008752	Sunderland 033C	5147	2	4580	2	3126	1	8487	3	5007	2	3115	1
{8A78B2B0-1D33-5CB0-E053-6B04A8C0F504}	NE31 1HZ	140000	S	N	F	2019-04-09 00:00	E01008652	South Tyneside 009B	2699	1	3302	2	2176	1	4111	2	355	1	5663	2
{8A78B2B0-1D34-5CB0-E053-6B04A8C0F504}	NE29 6TP	113200	T	N	F	2019-05-10 00:00	E01008544	North Tyneside 027D	864	1	673	1	426	1	494	1	1323	1	6646	3
{8A78B2B0-1D35-5CB0-E053-6B04A8C0F504}	NE27 0DG	127000	S	N	F	2019-05-10 00:00	E01008501	North Tyneside 018D	25440	8	25168	8	23644	8	18855	6	16062	5	25346	8
{8A78B2B0-1D36-5CB0-E053-6B04A8C0F504}	DH4 7TZ	300000	D	N	F	2019-05-17 00:00	E01008797	Sunderland 030C	22701	7	24811	8	16513	6	16838	6	14536	5	26073	8
{8A78B2B0-1D37-5CB0-E053-6B04A8C0F504}	NE28 7JS	270000	D	N	F	2019-04-26 00:00	E01008576	North Tyneside 029D	6765	3	4703	2	5817	2	11003	4	6336	2	8792	3
{8A78B2B0-1D38-5CB0-E053-6B04A8C0F504}	NE6 5DT	117000	F	N	L	2019-04-18 00:00	E01008360	Newcastle upon Tyne 018C	21835	7	19647	6	23505	8	17739	6	6063	2	31157	10
{8A78B2B0-1D39-5CB0-E053-6B04A8C0F504}	NE32 4SF	90000	S	N	F	2019-05-03 00:00	E01008632	South Tyneside 017B	5825	2	4516	2	3525	2	12913	4	3144	1	7375	3
{8A78B2B0-1D3A-5CB0-E053-6B04A8C0F504}	NE2 2BP	156000	F	N	L	2019-04-18 00:00	E01008369	Newcastle upon Tyne 013B	26386	9	31641	10	31416	10	12300	4	9730	3	30308	10
{8A78B2B0-1D3B-5CB0-E053-6B04A8C0F504}	NE16 5BE	245000	T	N	L	2019-04-25 00:00	E01008275	Gateshead 017E	29115	9	32472	10	28981	9	30642	10	14495	5	29569	10
{8A78B2B0-1D3C-5CB0-E053-6B04A8C0F504}	NE15 7TL	148000	S	N	F	2019-03-22 00:00	E01008416	Newcastle upon Tyne 025C	14353	5	13712	5	12346	4	4344	2	13161	5	15580	5
{8A78B2B0-1D3D-5CB0-E053-6B04A8C0F504}	NE3 1BQ	432500	T	N	F	2019-05-06 00:00	E01008418	Newcastle upon Tyne 005C	30892	10	32655	10	31897	10	11710	4	30418	10	32822	10
{8A78B2B0-1D3E-5CB0-E053-6B04A8C0F504}	NE9 6PW	99950	T	N	F	2019-04-30 00:00	E01008189	Gateshead 023A	2552	1	3212	1	1959	1	5968	2	1293	1	4664	2
{8A78B2B0-1D3F-5CB0-E053-6B04A8C0F504}	DH5 9BE	142000	D	N	F	2019-05-09 00:00	E01008748	Sunderland 035E	6931	3	8458	3	3256	1	5860	2	5051	2	11672	4
{8A78B2B0-1D40-5CB0-E053-6B04A8C0F504}	NE29 7HL	115950	T	N	F	2019-05-17 00:00	E01008482	North Tyneside 023B	2392	1	2447	1	1366	1	5692	2	1250	1	3647	2
{8A78B2B0-1D41-5CB0-E053-6B04A8C0F504}	NE34 8LS	88000	T	N	F	2019-04-29 00:00	E01008692	South Tyneside 019E	5943	2	5848	2	3778	2	13531	5	3526	2	5677	2
{8A78B2B0-1D42-5CB0-E053-6B04A8C0F504}	NE29 7DY	80000	F	N	L	2019-04-26 00:00	E01008492	North Tyneside 023E	4998	2	3881	2	3373	2	3896	2	7081	3	5154	2
{8A78B2B0-1D43-5CB0-E053-6B04A8C0F504}	NE9 5HJ	246000	S	N	F	2019-04-26 00:00	E01008237	Gateshead 016D	30305	10	31400	10	26733	9	17930	6	18290	6	31122	10
{8A78B2B0-1D44-5CB0-E053-6B04A8C0F504}	SR2 9HZ	235000	D	N	L	2019-04-30 00:00	E01008780	Sunderland 024D	6349	2	5078	2	3124	1	14797	5	2750	1	13105	4
{8A78B2B0-1D45-5CB0-E053-6B04A8C0F504}	NE28 8QQ	83000	F	N	L	2019-04-12 00:00	E01008535	North Tyneside 030B	13384	5	13824	5	10136	4	2463	1	13346	5	15684	5
{8A78B2B0-1D46-5CB0-E053-6B04A8C0F504}	NE17 7JL	52000	T	N	F	2019-04-17 00:00	E01008186	Gateshead 024B	3479	2	2912	1	1340	1	7717	3	3478	2	6437	2
{8A78B2B0-1D47-5CB0-E053-6B04A8C0F504}	NE27 0AY	95000	S	N	F	2019-05-21 00:00	E01008565	North Tyneside 007C	14346	5	13958	5	14343	5	9036	3	13334	5	15383	5
{8A78B2B0-1D48-5CB0-E053-6B04A8C0F504}	DH4 5AG	94000	T	N	F	2019-04-18 00:00	E01008754	Sunderland 034F	5325	2	5630	2	2980	1	3249	1	3023	1	8989	3
{8A78B2B0-1D49-5CB0-E053-6B04A8C0F504}	NE16 4BT	246000	D	N	F	2019-05-17 00:00	E01008264	Gateshead 009C	30610	10	29220	9	25112	8	24455	8	19974	7	30201	10
{8A78B2B0-1D4A-5CB0-E053-6B04A8C0F504}	NE16 3DF	80000	F	N	L	2019-03-29 00:00	E01008262	Gateshead 009A	7898	3	6646	3	4935	2	19708	7	2899	1	11479	4
{8A78B2B0-1D4B-5CB0-E053-6B04A8C0F504}	NE5 1DY	131000	S	N	L	2019-05-10 00:00	E01008328	Newcastle upon Tyne 015E	24916	8	28122	9	18044	6	16170	5	13790	5	23105	8
{8A78B2B0-1F6F-5CB0-E053-6B04A8C0F504}	NE3 2XG	160000	S	N	F	2019-04-30 00:00	E01008312	Newcastle upon Tyne 001F	26094	8	23266	8	22203	7	16331	5	18268	6	26378	9
{8A78B2B0-1F70-5CB0-E053-6B04A8C0F504}	NE3 3UL	363500	S	N	F	2019-04-29 00:00	E01008421	Newcastle upon Tyne 006F	31549	10	28924	9	28612	9	25695	8	23222	8	32739	10
{8A78B2B0-1F71-5CB0-E053-6B04A8C0F504}	NE15 7SJ	196000	T	N	F	2019-05-13 00:00	E01008386	Newcastle upon Tyne 021F	14193	5	11613	4	10599	4	22879	7	9862	4	10282	4
{8A78B2B0-1F72-5CB0-E053-6B04A8C0F504}	NE2 2SP	585000	T	N	F	2019-04-12 00:00	E01008369	Newcastle upon Tyne 013B	26386	9	31641	10	31416	10	12300	4	9730	3	30308	10
{8A78B2B0-1F73-5CB0-E053-6B04A8C0F504}	SR4 0ND	80000	S	N	F	2019-05-17 00:00	E01008811	Sunderland 014B	13209	5	11249	4	9865	4	13143	5	6425	2	12363	4
{8A78B2B0-1F74-5CB0-E053-6B04A8C0F504}	NE3 2FF	126000	T	N	L	2019-04-26 00:00	E01008294	Newcastle upon Tyne 001A	26280	9	22386	7	23326	8	24691	8	16777	6	24384	8
{8A78B2B0-1F75-5CB0-E053-6B04A8C0F504}	DH4 4TS	90000	T	N	F	2019-04-05 00:00	E01008796	Sunderland 032D	12257	4	10743	4	10381	4	5655	2	8713	3	11229	4
{8A78B2B0-1F76-5CB0-E053-6B04A8C0F504}	NE30 3ET	289950	S	N	F	2019-04-18 00:00	E01008497	North Tyneside 010C	32185	10	32187	10	29672	10	22973	7	21059	7	30504	10
{8A78B2B0-1F77-5CB0-E053-6B04A8C0F504}	NE15 6TN	132000	S	N	F	2019-02-27 00:00	E01033547	Newcastle upon Tyne 025E	649	1	633	1	797	1	3855	2	1428	1	206	1
{8A78B2B0-1F78-5CB0-E053-6B04A8C0F504}	NE32 3TW	110000	T	N	F	2019-04-18 00:00	E01008600	South Tyneside 007A	1089	1	581	1	934	1	5455	2	1679	1	998	1
{8A78B2B0-1F79-5CB0-E053-6B04A8C0F504}	NE27 0ED	83000	T	N	F	2019-04-26 00:00	E01008570	North Tyneside 011D	21743	7	18979	6	22397	7	31212	10	13089	4	14898	5
{8A78B2B0-1F7A-5CB0-E053-6B04A8C0F504}	NE16 5QJ	167500	S	N	F	2019-04-15 00:00	E01008270	Gateshead 017C	30235	10	29722	10	25673	8	26213	8	15693	5	28485	9
{8A78B2B0-1F7B-5CB0-E053-6B04A8C0F504}	NE28 9XZ	187000	D	N	L	2019-04-26 00:00	E01008466	North Tyneside 021B	29577	10	30492	10	25634	8	28183	9	18571	6	28298	9
{8A78B2B0-1F7C-5CB0-E053-6B04A8C0F504}	NE15 8DQ	93500	T	N	F	2019-04-18 00:00	E01008385	Newcastle upon Tyne 021E	3138	1	3851	2	3906	2	560	1	2673	1	3459	2
{8A78B2B0-1F7D-5CB0-E053-6B04A8C0F504}	NE40 3DH	150000	T	N	F	2019-05-17 00:00	E01008249	Gateshead 001D	22421	7	21737	7	16643	6	14894	5	10709	4	26831	9
{8A78B2B0-1F7E-5CB0-E053-6B04A8C0F504}	NE38 0LT	93000	T	N	F	2019-05-10 00:00	E01008868	Sunderland 020B	25948	8	23825	8	24086	8	26873	9	18743	6	20407	7
{8A78B2B0-1F7F-5CB0-E053-6B04A8C0F504}	SR2 8JJ	40000	T	N	F	2019-04-12 00:00	E01008737	Sunderland 016D	810	1	687	1	393	1	114	1	1011	1	7618	3
{8A78B2B0-1F80-5CB0-E053-6B04A8C0F504}	NE28 8TE	129950	S	N	L	2019-04-18 00:00	E01008534	North Tyneside 025C	21442	7	20343	7	17266	6	25474	8	14894	5	21449	7
{8A78B2B0-1F81-5CB0-E053-6B04A8C0F504}	NE34 0SF	202000	T	N	F	2019-04-30 00:00	E01008673	South Tyneside 003A	26235	8	26625	9	19600	6	20477	7	14037	5	29567	10
{8A78B2B0-1F82-5CB0-E053-6B04A8C0F504}	SR4 8BG	113000	T	N	F	2019-05-03 00:00	E01008813	Sunderland 014C	3778	2	3774	2	2502	1	6278	2	2118	1	3226	1
{8A78B2B0-1F83-5CB0-E053-6B04A8C0F504}	NE37 2ND	146000	S	N	F	2019-04-26 00:00	E01008856	Sunderland 007B	19409	6	19592	6	12317	4	29075	9	8827	3	20279	7
{8A78B2B0-1F85-5CB0-E053-6B04A8C0F504}	SR2 9DQ	154000	S	N	L	2019-05-22 00:00	E01008780	Sunderland 024D	6349	2	5078	2	3124	1	14797	5	2750	1	13105	4
{8A78B2B0-1F86-5CB0-E053-6B04A8C0F504}	NE33 4RJ	85000	T	N	F	2019-05-02 00:00	E01008590	South Tyneside 011A	2677	1	2760	1	1413	1	738	1	2923	1	7272	3
{8A78B2B0-1F87-5CB0-E053-6B04A8C0F504}	NE6 5UE	179500	S	N	F	2019-04-26 00:00	E01008363	Newcastle upon Tyne 012E	24663	8	23144	8	20204	7	22518	7	13165	5	27260	9
{8A78B2B0-1F88-5CB0-E053-6B04A8C0F504}	NE38 8RX	257000	D	N	F	2019-04-05 00:00	E01008861	Sunderland 025B	13353	5	12000	4	7852	3	23348	8	10947	4	11950	4
{8A78B2B0-1F89-5CB0-E053-6B04A8C0F504}	SR4 7RX	149950	T	N	F	2019-05-16 00:00	E01008760	Sunderland 018A	23330	8	21983	7	20471	7	15105	5	11527	4	23999	8
{8A78B2B0-1F8A-5CB0-E053-6B04A8C0F504}	SR4 7LY	30000	T	N	L	2019-05-10 00:00	E01008832	Sunderland 018C	11344	4	10973	4	11282	4	4972	2	7077	3	11199	4
{8A78B2B0-1F8B-5CB0-E053-6B04A8C0F504}	NE38 7HF	119950	S	N	F	2019-04-26 00:00	E01008848	Sunderland 019C	17790	6	19478	6	12431	4	11541	4	14916	5	18038	6
{8A78B2B0-1F8C-5CB0-E053-6B04A8C0F504}	NE34 9HB	185000	D	N	F	2019-04-24 00:00	E01008605	South Tyneside 016B	9344	3	8293	3	6943	3	7357	3	6912	3	10222	4
{8A78B2B0-1F8D-5CB0-E053-6B04A8C0F504}	NE33 3AG	85000	S	N	F	2019-03-12 00:00	E01008676	South Tyneside 003C	10251	4	8792	3	7519	3	9146	3	4510	2	15023	5
{8A78B2B0-1F8E-5CB0-E053-6B04A8C0F504}	NE5 5JU	129000	S	N	F	2019-04-25 00:00	E01008441	Newcastle upon Tyne 031A	5826	2	5753	2	4187	2	10622	4	2386	1	7088	3
{8A78B2B0-1F8F-5CB0-E053-6B04A8C0F504}	NE13 6HJ	97000	S	N	F	2019-04-30 00:00	E01008582	North Tyneside 004E	13897	5	10348	4	12301	4	15610	5	12451	4	9165	3
{8A78B2B0-1F90-5CB0-E053-6B04A8C0F504}	SR6 7DT	122000	S	N	F	2019-05-17 00:00	E01008687	South Tyneside 018E	16700	6	10383	4	8523	3	26470	9	14872	5	20076	7
{85866A64-ACAE-143F-E053-6B04A8C06A15}	SS8 0HF	357500	D	N	F	2019-02-19 00:00	E01021501	Castle Point 011D	14681	5	12209	4	12794	4	20250	7	15058	5	7418	3
{85866A64-ACAF-143F-E053-6B04A8C06A15}	CM4 9AG	498000	D	N	F	2019-03-08 00:00	E01021459	Brentwood 002C	32201	10	31920	10	30181	10	18542	6	31865	10	30219	10
{85866A64-ACB0-143F-E053-6B04A8C06A15}	CM1 2RL	190000	F	N	L	2019-02-15 00:00	E01033138	Chelmsford 009F	27058	9	24682	8	25781	8	16392	5	25995	8	24558	8
{85866A64-ACB2-143F-E053-6B04A8C06A15}	CM18 7RN	140000	F	N	L	2019-03-13 00:00	E01021859	Harlow 010C	8483	3	6988	3	7551	3	7730	3	10544	4	5476	2
{85866A64-ACB3-143F-E053-6B04A8C06A15}	CM17 0HR	345000	T	N	F	2019-03-19 00:00	E01021854	Harlow 001A	16040	5	15503	5	14436	5	10355	4	11724	4	12800	4
{85866A64-ACB6-143F-E053-6B04A8C06A15}	CB11 4PF	200000	S	N	F	2019-02-27 00:00	E01022061	Uttlesford 003A	29300	9	29397	9	32263	10	25259	8	32651	10	29587	10
{85866A64-ACB7-143F-E053-6B04A8C06A15}	RM3 0SL	390000	T	N	F	2019-03-19 00:00	E01002298	Havering 007D	22608	7	18694	6	20816	7	18788	6	26407	9	17385	6
{85866A64-ACB8-143F-E053-6B04A8C06A15}	CO15 1BP	169000	T	N	F	2019-02-08 00:00	E01022036	Tendring 017C	10441	4	13918	5	12175	4	5246	2	9941	4	6681	3
{85866A64-ACB9-143F-E053-6B04A8C06A15}	SS9 5RY	350000	D	N	F	2019-02-28 00:00	E01015833	Southend-on-Sea 001A	28336	9	25242	8	24389	8	27372	9	21716	7	18613	6
{85866A64-ACBB-143F-E053-6B04A8C06A15}	SS8 9EA	220000	D	N	F	2019-02-22 00:00	E01021484	Castle Point 011A	14562	5	14943	5	12297	4	11254	4	20691	7	5025	2
{85866A64-ACBC-143F-E053-6B04A8C06A15}	CM6 2NE	780000	D	N	F	2019-02-21 00:00	E01022092	Uttlesford 004A	25008	8	28509	9	26463	9	25527	8	31322	10	21542	7
{85866A64-ACBE-143F-E053-6B04A8C06A15}	SS11 7EF	365950	T	N	F	2019-03-11 00:00	E01021334	Basildon 005A	21388	7	20964	7	18908	6	12047	4	19484	6	14391	5
{85866A64-ACC1-143F-E053-6B04A8C06A15}	CO4 9UN	665995	D	N	F	2019-03-11 00:00	E01021671	Colchester 002D	22155	7	19436	6	15416	5	23811	8	14026	5	27648	9
{85866A64-ACC2-143F-E053-6B04A8C06A15}	CO15 2RZ	70000	D	N	F	2019-02-18 00:00	E01021990	Tendring 018C	1514	1	1637	1	1100	1	6831	3	1626	1	595	1
{85866A64-ACC3-143F-E053-6B04A8C06A15}	SS4 3HX	255000	S	N	F	2019-02-25 00:00	E01021929	Rochford 002D	32073	10	30772	10	28278	9	29962	10	31121	10	23829	8
{85866A64-ACC4-143F-E053-6B04A8C06A15}	SS13 1RT	280000	T	N	F	2019-02-22 00:00	E01021308	Basildon 011D	16676	6	19383	6	19510	6	9418	3	17374	6	6538	2
{85866A64-ACC5-143F-E053-6B04A8C06A15}	CM2 6XD	210000	F	N	L	2019-02-14 00:00	E01021547	Chelmsford 008D	25778	8	25894	8	28741	9	20458	7	30373	10	26522	9
{85866A64-ACC6-143F-E053-6B04A8C06A15}	CO1 2BL	200000	T	N	F	2019-03-08 00:00	E01021686	Colchester 011D	5142	2	4162	2	6526	2	5571	2	5536	2	10119	4
{85866A64-ACC7-143F-E053-6B04A8C06A15}	CM22 7JB	553500	D	N	F	2019-03-08 00:00	E01022059	Uttlesford 009A	24749	8	27480	9	30026	10	14338	5	31260	10	23266	8
{85866A64-ACC8-143F-E053-6B04A8C06A15}	CM15 9NR	242000	T	N	F	2019-02-07 00:00	E01021461	Brentwood 004D	12860	4	10654	4	12049	4	10625	4	17909	6	6332	2
{85866A64-ACCA-143F-E053-6B04A8C06A15}	CM2 6UB	163000	F	N	L	2019-01-25 00:00	E01021547	Chelmsford 008D	25778	8	25894	8	28741	9	20458	7	30373	10	26522	9
{85866A64-ACCB-143F-E053-6B04A8C06A15}	CM4 9EG	610000	S	N	F	2019-02-22 00:00	E01021458	Brentwood 002B	29814	10	24676	8	26869	9	19759	7	29379	9	26933	9
{85866A64-ACCC-143F-E053-6B04A8C06A15}	CM2 0TL	540000	S	N	F	2019-02-15 00:00	E01021577	Chelmsford 012B	28378	9	26088	8	25194	8	13262	5	30271	10	29274	9
{85866A64-ACCD-143F-E053-6B04A8C06A15}	CO15 2NN	214000	D	N	F	2019-01-31 00:00	E01021990	Tendring 018C	1514	1	1637	1	1100	1	6831	3	1626	1	595	1
{85866A64-ACCF-143F-E053-6B04A8C06A15}	CO16 8RY	290000	D	N	F	2019-02-15 00:00	E01022045	Tendring 018D	1253	1	2878	1	1500	1	278	1	2165	1	5405	2
{85866A64-ACD0-143F-E053-6B04A8C06A15}	CO15 3HP	177000	T	N	F	2019-02-19 00:00	E01021970	Tendring 016A	419	1	833	1	435	1	486	1	643	1	1351	1
{85866A64-ACD1-143F-E053-6B04A8C06A15}	CO15 4LE	158000	S	N	F	2019-03-13 00:00	E01022041	Tendring 010D	10272	4	10967	4	6448	2	12709	4	8289	3	5681	2
{85866A64-AED5-143F-E053-6B04A8C06A15}	CM2 6YZ	385000	S	N	F	2019-02-06 00:00	E01021545	Chelmsford 008B	29733	10	28677	9	30068	10	20979	7	28283	9	21924	7
{85866A64-AED6-143F-E053-6B04A8C06A15}	CO6 2SB	258000	D	N	F	2019-03-21 00:00	E01021410	Braintree 006E	15398	5	10005	4	10628	4	27988	9	15396	5	11591	4
{85866A64-AED8-143F-E053-6B04A8C06A15}	CM2 8PX	249000	T	N	F	2019-01-21 00:00	E01021552	Chelmsford 017A	22220	7	19856	7	19300	6	19943	7	24141	8	13976	5
{85866A64-AED9-143F-E053-6B04A8C06A15}	CB11 4FG	875000	D	N	F	2019-02-14 00:00	E01022075	Uttlesford 001B	32811	10	32586	10	32740	10	30019	10	31890	10	32488	10
{85866A64-AEDA-143F-E053-6B04A8C06A15}	CO16 9DT	100000	S	N	F	2019-02-15 00:00	E01022018	Tendring 007E	10827	4	13702	5	8241	3	16597	6	6683	3	7691	3
{85866A64-AEDB-143F-E053-6B04A8C06A15}	CM7 1XF	345000	D	N	F	2019-03-22 00:00	E01021373	Braintree 011D	18595	6	15456	5	14374	5	21445	7	21176	7	11426	4
{85866A64-AEDC-143F-E053-6B04A8C06A15}	CM2 9NF	246500	T	N	F	2019-03-08 00:00	E01021585	Chelmsford 015D	31111	10	30824	10	30373	10	27324	9	31460	10	17808	6
{85866A64-AEDD-143F-E053-6B04A8C06A15}	CM2 8BN	385000	S	N	F	2019-02-15 00:00	E01021559	Chelmsford 017E	30472	10	30985	10	29952	10	30250	10	30234	10	26742	9
{85866A64-AEDE-143F-E053-6B04A8C06A15}	CM17 9WH	270000	T	N	F	2019-02-25 00:00	E01021828	Harlow 005E	29026	9	28726	9	31670	10	30082	10	26399	9	19091	6
{85866A64-AEDF-143F-E053-6B04A8C06A15}	CO13 0PT	235000	S	N	F	2019-02-14 00:00	E01022009	Tendring 008E	14233	5	14656	5	12164	4	24084	8	9331	3	11562	4
{85866A64-AEE0-143F-E053-6B04A8C06A15}	CO15 6AE	189995	F	N	L	2019-01-25 00:00	E01022027	Tendring 016D	1294	1	3683	2	1076	1	598	1	1515	1	4282	2
{85866A64-AEE2-143F-E053-6B04A8C06A15}	RM19 1SA	235000	T	N	F	2019-01-25 00:00	E01016012	Thurrock 015C	10896	4	12837	4	17782	6	4963	2	17870	6	10767	4
{85866A64-AEE3-143F-E053-6B04A8C06A15}	SS2 4LQ	180000	F	N	L	2019-02-28 00:00	E01015875	Southend-on-Sea 006G	3734	2	3197	1	2319	1	4807	2	5037	2	5011	2
{85866A64-AEE4-143F-E053-6B04A8C06A15}	SS3 0BG	288000	S	N	F	2019-03-08 00:00	E01021923	Rochford 010D	26100	8	23882	8	21637	7	22909	7	26157	8	12612	4
{85866A64-AEE6-143F-E053-6B04A8C06A15}	IG7 5NF	195000	F	N	L	2019-02-20 00:00	E01021764	Epping Forest 017A	9597	3	5799	2	10191	4	11898	4	16888	6	6711	3
{85866A64-AEE7-143F-E053-6B04A8C06A15}	CM11 1ND	329000	S	N	F	2019-02-15 00:00	E01021604	Chelmsford 018D	24703	8	27375	9	30125	10	14388	5	32261	10	24088	8
{85866A64-AEE8-143F-E053-6B04A8C06A15}	CM2 7LL	367500	S	N	F	2019-02-15 00:00	E01021564	Chelmsford 013D	29223	9	27928	9	23489	8	17722	6	29895	10	24257	8
{85866A64-AEE9-143F-E053-6B04A8C06A15}	SS3 9UP	430000	D	N	F	2019-03-14 00:00	E01015881	Southend-on-Sea 013F	19853	7	15780	5	14860	5	15631	5	21976	7	13696	5
{85866A64-AEEA-143F-E053-6B04A8C06A15}	CO4 0AT	155000	F	N	L	2019-03-22 00:00	E01021702	Colchester 022D	20886	7	18375	6	24539	8	12433	4	19004	6	16201	5
{85866A64-AEEB-143F-E053-6B04A8C06A15}	SS8 7SN	195000	S	N	F	2019-03-05 00:00	E01021497	Castle Point 012D	14538	5	13598	5	15491	5	21146	7	18078	6	3213	1
{85866A64-AEEC-143F-E053-6B04A8C06A15}	RM16 6BY	225000	F	N	L	2019-03-01 00:00	E01015982	Thurrock 019A	27368	9	27768	9	30257	10	15036	5	25345	8	26687	9
{85866A64-AEED-143F-E053-6B04A8C06A15}	CM8 3RP	267000	S	N	F	2019-02-08 00:00	E01021360	Braintree 012A	14463	5	11036	4	11786	4	19396	6	15817	5	5774	2
{85866A64-AEEE-143F-E053-6B04A8C06A15}	CO5 7EA	222000	T	N	F	2019-03-20 00:00	E01021657	Colchester 016A	21358	7	18702	6	18764	6	20922	7	19172	6	19681	6
{85866A64-AEEF-143F-E053-6B04A8C06A15}	CO7 6AW	450000	S	N	F	2019-03-06 00:00	E01021656	Colchester 001B	21899	7	20953	7	21581	7	22662	7	29877	10	24087	8
{85866A64-AEF1-143F-E053-6B04A8C06A15}	CB9 7DX	202800	T	N	F	2019-03-08 00:00	E01021375	Braintree 001A	25740	8	25001	8	19676	6	26546	9	23642	8	22541	7
{85866A64-AEF3-143F-E053-6B04A8C06A15}	CM6 1LX	415000	S	N	F	2019-03-18 00:00	E01022058	Uttlesford 008A	20459	7	27552	9	28262	9	29918	10	29027	9	25412	8
{85866A64-AEF5-143F-E053-6B04A8C06A15}	SS3 0EQ	202500	F	N	L	2019-03-22 00:00	E01021923	Rochford 010D	26100	8	23882	8	21637	7	22909	7	26157	8	12612	4
{85866A64-AEF6-143F-E053-6B04A8C06A15}	CM16 7QQ	1000000	F	N	L	2019-03-15 00:00	E01021800	Epping Forest 003C	9468	3	20310	7	19901	7	5635	2	26159	8	10987	4
{85866A64-AEF7-143F-E053-6B04A8C06A15}	CM1 6NF	225500	F	N	L	2019-02-25 00:00	E01021624	Chelmsford 004F	32035	10	32354	10	28950	9	24488	8	29662	10	23772	8
{85866A64-AEF8-143F-E053-6B04A8C06A15}	CO15 4BT	320000	D	N	F	2019-02-22 00:00	E01022042	Tendring 014A	1299	1	965	1	1030	1	4672	2	1943	1	1378	1
{85866A64-AEF9-143F-E053-6B04A8C06A15}	CO12 5FG	336000	D	N	F	2019-03-01 00:00	E01022002	Tendring 004C	16473	6	15310	5	12675	4	26099	8	11942	4	9408	3
{85866A64-AEFA-143F-E053-6B04A8C06A15}	SS9 1LT	210000	F	N	L	2019-03-08 00:00	E01015830	Southend-on-Sea 012D	31888	10	30955	10	29338	9	15439	5	31062	10	30053	10
{85866A64-AA79-143F-E053-6B04A8C06A15}	CB10 2BB	307500	S	N	F	2019-02-15 00:00	E01022079	Uttlesford 002D	25552	8	21904	7	23115	8	23823	8	29948	10	23044	8
{85866A64-AA7A-143F-E053-6B04A8C06A15}	CM0 8TL	247500	S	N	F	2019-03-06 00:00	E01021878	Maldon 008C	24234	8	17330	6	20968	7	23454	8	22276	7	17718	6
{85866A64-AA7B-143F-E053-6B04A8C06A15}	CM3 5TS	280000	S	N	F	2019-01-25 00:00	E01021611	Chelmsford 019A	29960	10	29487	9	27772	9	27886	9	31237	10	19667	6
{85866A64-AA7C-143F-E053-6B04A8C06A15}	CM16 5DP	407000	S	N	F	2019-02-21 00:00	E01021763	Epping Forest 005D	23322	8	19500	6	20336	7	10121	4	27743	9	23132	8
{85866A64-AA7D-143F-E053-6B04A8C06A15}	CO7 9HW	255000	S	N	F	2019-03-06 00:00	E01021737	Colchester 017B	22925	7	22881	7	22398	7	31210	10	18304	6	20513	7
{85866A64-AA7E-143F-E053-6B04A8C06A15}	SS4 3BG	284000	S	N	F	2019-03-08 00:00	E01021928	Rochford 002C	24932	8	19758	7	22636	7	25751	8	28958	9	13218	5
{85866A64-AA7F-143F-E053-6B04A8C06A15}	CO7 7YH	260000	S	N	F	2019-02-15 00:00	E01022052	Tendring 005D	19412	6	18796	6	13021	4	31188	10	11178	4	17452	6
{85866A64-AA80-143F-E053-6B04A8C06A15}	IG10 3TU	410000	S	N	F	2019-02-22 00:00	E01021775	Epping Forest 011B	10606	4	12393	4	10697	4	1953	1	17673	6	7365	3
{85866A64-AA82-143F-E053-6B04A8C06A15}	CO3 9XW	295000	D	N	F	2019-02-18 00:00	E01021690	Colchester 014B	24250	8	22116	7	20119	7	27771	9	19820	7	21705	7
{85866A64-AA83-143F-E053-6B04A8C06A15}	CM15 0XE	445000	T	N	F	2019-03-14 00:00	E01021443	Brentwood 001C	14807	5	15059	5	23251	8	12093	4	29455	9	11836	4
{85866A64-AA84-143F-E053-6B04A8C06A15}	CO15 4EU	182000	D	N	F	2019-03-01 00:00	E01022044	Tendring 013E	6985	3	7189	3	4225	2	12849	4	5916	2	4758	2
{85866A64-AA85-143F-E053-6B04A8C06A15}	SS13 3HW	238500	T	N	F	2019-02-07 00:00	E01021317	Basildon 018E	2634	1	3656	2	3905	2	315	1	7082	3	1511	1
{85866A64-AA86-143F-E053-6B04A8C06A15}	SS5 4UN	370000	S	N	F	2019-03-12 00:00	E01021941	Rochford 003I	31708	10	30948	10	30664	10	29011	9	32310	10	22070	7
{85866A64-AA87-143F-E053-6B04A8C06A15}	SS15 5QE	353250	D	N	F	2019-03-15 00:00	E01021274	Basildon 010D	11620	4	10986	4	11700	4	7092	3	12932	4	7759	3
{85866A64-AA88-143F-E053-6B04A8C06A15}	CM22 6LT	275000	S	N	F	2019-02-08 00:00	E01022062	Uttlesford 005A	31238	10	31540	10	31591	10	25528	8	32376	10	27406	9
{85866A64-AA89-143F-E053-6B04A8C06A15}	CM1 6QR	146000	F	N	L	2019-02-26 00:00	E01021621	Chelmsford 007B	23198	8	23852	8	26567	9	15829	5	30199	10	15917	5
{85866A64-AA8A-143F-E053-6B04A8C06A15}	CM15 9LX	268000	T	N	F	2019-01-25 00:00	E01021461	Brentwood 004D	12860	4	10654	4	12049	4	10625	4	17909	6	6332	2
{85866A64-AA8B-143F-E053-6B04A8C06A15}	CM12 0UD	450000	D	N	F	2019-03-01 00:00	E01021252	Basildon 002E	30593	10	31139	10	31725	10	28838	9	24869	8	28950	9
{85866A64-AA8C-143F-E053-6B04A8C06A15}	EN9 2LF	377500	T	N	F	2019-02-28 00:00	E01021794	Epping Forest 002D	17854	6	13753	5	22056	7	13446	5	23832	8	10957	4
{85866A64-AA8E-143F-E053-6B04A8C06A15}	SS16 5EH	251500	T	N	F	2019-03-14 00:00	E01021296	Basildon 020C	12969	4	12018	4	11559	4	3827	2	19569	6	11857	4
{85866A64-AA8F-143F-E053-6B04A8C06A15}	IG6 2QU	529000	T	N	F	2019-03-07 00:00	E01003700	Redbridge 006C	16080	5	14281	5	14975	5	12573	4	22969	7	14790	5
{85866A64-AA90-143F-E053-6B04A8C06A15}	CM3 5UA	360000	D	N	F	2019-02-22 00:00	E01021611	Chelmsford 019A	29960	10	29487	9	27772	9	27886	9	31237	10	19667	6
{85866A64-AA91-143F-E053-6B04A8C06A15}	SS13 3EN	250000	T	N	F	2019-03-01 00:00	E01021317	Basildon 018E	2634	1	3656	2	3905	2	315	1	7082	3	1511	1
{85866A64-AA92-143F-E053-6B04A8C06A15}	SS15 5EP	290000	T	N	F	2019-02-20 00:00	E01021292	Basildon 017B	3402	2	3303	2	2862	1	379	1	7041	3	5827	2
{85866A64-AA93-143F-E053-6B04A8C06A15}	IG10 3PY	365000	T	N	F	2019-03-06 00:00	E01021771	Epping Forest 013A	5221	2	4339	2	5344	2	7090	3	12147	4	3244	1
{85866A64-AA94-143F-E053-6B04A8C06A15}	RM15 5QA	266000	T	N	F	2019-03-20 00:00	E01015927	Thurrock 007A	9921	4	7322	3	10173	4	6962	3	17341	6	6118	2
{85866A64-AA95-143F-E053-6B04A8C06A15}	CM6 1HG	345000	F	N	F	2019-03-08 00:00	E01022067	Uttlesford 007B	21988	7	16739	6	18171	6	23066	8	21253	7	17256	6
{85866A64-AA96-143F-E053-6B04A8C06A15}	SS13 2DY	295000	S	N	F	2019-03-25 00:00	E01021313	Basildon 018A	13200	5	19275	6	14851	5	4237	2	12298	4	9836	3
{85866A64-AA97-143F-E053-6B04A8C06A15}	SS16 5EQ	260000	T	N	F	2019-02-06 00:00	E01021296	Basildon 020C	12969	4	12018	4	11559	4	3827	2	19569	6	11857	4
{85866A64-AA98-143F-E053-6B04A8C06A15}	CB11 3LZ	1200000	D	N	F	2019-03-01 00:00	E01022099	Uttlesford 004D	29390	9	32097	10	32115	10	30826	10	32431	10	28089	9
{85866A64-AA9A-143F-E053-6B04A8C06A15}	SS2 6SP	305000	S	N	F	2019-02-15 00:00	E01015868	Southend-on-Sea 002F	8729	3	7994	3	8780	3	10202	4	12151	4	3963	2
{85866A64-AA9B-143F-E053-6B04A8C06A15}	CO6 1BB	288000	D	N	F	2019-03-14 00:00	E01021662	Colchester 010B	20670	7	22343	7	18360	6	29971	10	24396	8	21794	7
{85866A64-ACD3-143F-E053-6B04A8C06A15}	SS6 8JE	315000	D	N	F	2019-03-22 00:00	E01021962	Rochford 008C	18963	6	14646	5	21075	7	14471	5	25930	8	11135	4
{85866A64-ACD4-143F-E053-6B04A8C06A15}	CO13 0LZ	192500	S	N	F	2019-03-01 00:00	E01022010	Tendring 008F	15831	5	15039	5	10479	4	26205	8	13626	5	9694	3
{85866A64-ACD5-143F-E053-6B04A8C06A15}	CO2 9NX	222000	T	N	F	2019-02-08 00:00	E01021714	Colchester 015D	17127	6	16855	6	15398	5	18497	6	14036	5	11772	4
{85866A64-ACD6-143F-E053-6B04A8C06A15}	SS8 8EQ	250000	S	N	F	2019-02-28 00:00	E01021493	Castle Point 009B	16118	5	14734	5	15342	5	15641	5	20484	7	7486	3
{85866A64-ACD7-143F-E053-6B04A8C06A15}	CO13 9AS	315000	F	N	L	2019-02-28 00:00	E01021986	Tendring 006B	17345	6	18319	6	12566	4	12083	4	12841	4	18560	6
{85866A64-ACD8-143F-E053-6B04A8C06A15}	EN9 1BL	300000	T	N	F	2019-01-31 00:00	E01021818	Epping Forest 009C	13781	5	11077	4	11471	4	9618	3	20122	7	12714	4
{85866A64-ACD9-143F-E053-6B04A8C06A15}	IG9 6BU	807000	S	N	F	2019-02-20 00:00	E01021742	Epping Forest 015A	19657	6	15116	5	16939	6	11962	4	24570	8	15892	5
{85866A64-ACDA-143F-E053-6B04A8C06A15}	SS7 3UL	312500	S	N	F	2019-03-01 00:00	E01021510	Castle Point 002B	22348	7	20969	7	19176	6	30215	10	15534	5	14229	5
{85866A64-ACDB-143F-E053-6B04A8C06A15}	SS4 1TX	135000	F	N	L	2019-03-04 00:00	E01021930	Rochford 007A	17611	6	16685	6	13250	5	23771	8	18878	6	12833	4
{85866A64-ACDC-143F-E053-6B04A8C06A15}	CM3 5QE	380000	S	N	F	2019-02-22 00:00	E01021614	Chelmsford 019D	31259	10	27688	9	30142	10	25582	8	30841	10	18963	6
{85866A64-ACDD-143F-E053-6B04A8C06A15}	CO6 1HN	195000	T	N	F	2019-02-21 00:00	E01021678	Colchester 010E	16239	5	21261	7	16025	5	6227	2	19012	6	17159	6
{85866A64-ACDE-143F-E053-6B04A8C06A15}	CO15 5XU	200000	S	N	F	2019-03-22 00:00	E01022033	Tendring 012B	11303	4	9315	3	7462	3	26175	8	7716	3	7552	3
{85866A64-ACDF-143F-E053-6B04A8C06A15}	SS8 9RD	566500	D	N	F	2019-02-26 00:00	E01021505	Castle Point 008D	22633	7	24378	8	20780	7	15769	5	20594	7	9299	3
{85866A64-ACE0-143F-E053-6B04A8C06A15}	RM1 4DU	390000	S	N	F	2019-02-22 00:00	E01002334	Havering 008B	22951	7	20365	7	27498	9	12905	4	30122	10	16703	6
{8F1B26BD-4597-53DB-E053-6C04A8C03649}	N22 7AQ	575000	F	N	L	2019-07-12 00:00	E01001962	Haringey 004A	18441	6	15087	5	20622	7	13125	4	24951	8	29142	9
{8F1B26BD-4598-53DB-E053-6C04A8C03649}	E8 1FR	709000	F	N	L	2019-06-21 00:00	E01001762	Hackney 017D	9543	3	11630	4	12792	4	11315	4	10464	4	28052	9
{8F1B26BD-4599-53DB-E053-6C04A8C03649}	E10 6JE	300000	F	N	L	2019-07-01 00:00	E01004367	Waltham Forest 019D	9423	3	11525	4	12972	4	3874	2	16699	6	13087	4
{8F1B26BD-459A-53DB-E053-6C04A8C03649}	E10 6PB	410000	F	N	L	2019-06-27 00:00	E01004372	Waltham Forest 023C	22386	7	24738	8	30666	10	24263	8	24401	8	22697	7
{8F1B26BD-459B-53DB-E053-6C04A8C03649}	EN2 8LA	1000000	F	N	L	2019-06-21 00:00	E01001412	Enfield 004C	8853	3	10956	4	13733	5	5796	2	26509	9	13225	5
{8F1B26BD-459D-53DB-E053-6C04A8C03649}	E3 4NA	415000	F	N	L	2019-06-25 00:00	E01004267	Tower Hamlets 012D	6672	3	4497	2	9591	3	2294	1	14406	5	23029	8
{8F1B26BD-459E-53DB-E053-6C04A8C03649}	E11 1PL	415000	F	N	L	2019-05-31 00:00	E01004468	Waltham Forest 015E	16258	5	18667	6	22110	7	10169	4	24560	8	22659	7
{8F1B26BD-459F-53DB-E053-6C04A8C03649}	W4 5AG	1075000	F	N	L	2019-07-05 00:00	E01002692	Hounslow 029C	17842	6	16096	5	20186	7	16367	5	28761	9	26761	9
{8F1B26BD-45A1-53DB-E053-6C04A8C03649}	E2 6AT	600000	F	N	L	2019-06-21 00:00	E01004313	Tower Hamlets 009B	11032	4	8127	3	15213	5	11763	4	15811	5	17146	6
{8F1B26BD-45A2-53DB-E053-6C04A8C03649}	E8 1AB	470000	F	N	L	2019-07-17 00:00	E01001763	Hackney 020C	12683	4	12525	4	20885	7	11700	4	20253	7	22081	7
{8F1B26BD-45A3-53DB-E053-6C04A8C03649}	E17 6LZ	400000	T	N	L	2019-07-05 00:00	E01004393	Waltham Forest 014B	12894	4	11571	4	20234	7	16076	5	14785	5	21131	7
{8F1B26BD-45A4-53DB-E053-6C04A8C03649}	E17 5SB	240000	F	N	L	2019-06-21 00:00	E01004400	Waltham Forest 009C	8395	3	8027	3	10436	4	8140	3	17094	6	13196	5
{8F1B26BD-45A5-53DB-E053-6C04A8C03649}	W4 2RZ	360000	F	N	L	2019-05-31 00:00	E01002572	Hounslow 007B	7879	3	5815	2	7673	3	12416	4	8490	3	15172	5
{8F1B26BD-45A6-53DB-E053-6C04A8C03649}	N4 2GQ	640000	F	N	L	2019-06-28 00:00	E01033701	Hackney 002F	2578	1	1749	1	5333	2	4868	2	11339	4	8128	3
{8F1B26BD-45A7-53DB-E053-6C04A8C03649}	N5 1TU	420000	F	N	L	2019-07-18 00:00	E01002752	Islington 009E	12440	4	8376	3	10958	4	10110	4	17498	6	23012	8
{8F1B26BD-45A8-53DB-E053-6C04A8C03649}	N22 6RR	340295	F	N	L	2019-06-28 00:00	E01002027	Haringey 010A	8044	3	6864	3	8658	3	8530	3	13450	5	13056	4
{8F1B26BD-45A9-53DB-E053-6C04A8C03649}	NW2 4ES	582500	F	N	L	2019-06-07 00:00	E01000560	Brent 023D	15170	5	16020	5	15775	5	9069	3	24133	8	25820	8
{8F1B26BD-45AA-53DB-E053-6C04A8C03649}	E4 9RH	922000	T	N	F	2019-07-04 00:00	E01004386	Waltham Forest 003C	25868	8	27219	9	24801	8	17798	6	25645	8	22079	7
{8F1B26BD-45AB-53DB-E053-6C04A8C03649}	UB9 6RD	660000	D	N	F	2019-03-06 00:00	E01002441	Hillingdon 003D	11576	4	10413	4	12737	4	5963	2	11847	4	11870	4
{8F1B26BD-45AC-53DB-E053-6C04A8C03649}	EN4 9SE	322000	F	N	L	2019-07-05 00:00	E01000170	Barnet 006A	14031	5	10719	4	10414	4	8594	3	25024	8	21554	7
{8F1B26BD-45AD-53DB-E053-6C04A8C03649}	N14 4JR	385000	F	N	L	2019-06-28 00:00	E01001525	Enfield 020E	17196	6	15368	5	19559	6	15865	5	23866	8	27045	9
{8F1B26BD-45AE-53DB-E053-6C04A8C03649}	E1 8RB	395000	F	N	L	2019-06-14 00:00	E01000005	City of London 001E	8678	3	6029	2	7833	3	31059	10	17907	6	12370	4
{8F1B26BD-45AF-53DB-E053-6C04A8C03649}	TW14 8PB	228000	F	N	L	2019-05-31 00:00	E01002557	Hounslow 023A	10494	4	11062	4	14669	5	10900	4	20088	7	8779	3
{8F1B26BD-45B0-53DB-E053-6C04A8C03649}	W5 2PZ	696500	F	N	L	2019-05-29 00:00	E01001235	Ealing 020D	19722	7	19912	7	24417	8	7228	3	23433	8	24888	8
{8F1B26BD-45B1-53DB-E053-6C04A8C03649}	NW9 0FG	470000	F	N	L	2019-04-01 00:00	E01000516	Brent 002C	14898	5	15553	5	19342	6	10621	4	23970	8	16778	6
{8F1B26BD-45B2-53DB-E053-6C04A8C03649}	HA5 1SL	725000	D	N	F	2019-06-27 00:00	E01002437	Hillingdon 006E	29735	10	28358	9	30166	10	25370	8	30225	10	31182	10
{8F1B26BD-45B3-53DB-E053-6C04A8C03649}	N6 4EY	800000	F	N	L	2019-04-26 00:00	E01002011	Haringey 030D	13214	5	13895	5	14301	5	4212	2	23360	8	24177	8
{8F1B26BD-45B4-53DB-E053-6C04A8C03649}	E4 9XE	208000	F	N	L	2019-07-01 00:00	E01004419	Waltham Forest 008E	13460	5	18459	6	20853	7	9748	3	26058	8	17203	6
{9B361206-17BF-1904-E053-6B04A8C0EEB5}	TQ6 0EX	540000	T	N	F	2019-12-06 00:00	E01020188	South Hams 004D	17489	6	23907	8	25303	8	29674	10	28820	9	28651	9
{9B361206-17C0-1904-E053-6B04A8C0EEB5}	EX7 0LS	315000	D	N	F	2019-11-29 00:00	E01020231	Teignbridge 005C	18779	6	17483	6	15104	5	25394	8	16218	5	10636	4
{9B361206-17C1-1904-E053-6B04A8C0EEB5}	EX37 9RL	600000	D	N	F	2019-12-02 00:00	E01020097	North Devon 013A	13309	5	20899	7	25133	8	31411	10	25704	8	16223	5
{9FF0D969-6881-11ED-E053-6C04A8C06383}	TW7 6JT	383000	F	N	L	2019-10-11 00:00	E01002658	Hounslow 015D	24569	8	27868	9	30583	10	12728	4	22019	7	29033	9
{9B361206-17C3-1904-E053-6B04A8C0EEB5}	EX12 2SS	210000	D	N	F	2019-11-12 00:00	E01019949	East Devon 010D	28437	9	23171	8	22391	7	31761	10	29255	9	19749	7
{9B361206-17C4-1904-E053-6B04A8C0EEB5}	EX2 7NQ	329950	T	Y	F	2019-08-06 00:00	E01020033	Exeter 015C	17593	6	12417	4	11876	4	17951	6	20467	7	20861	7
{9B361206-17C5-1904-E053-6B04A8C0EEB5}	PL20 7PD	225000	T	N	F	2019-12-16 00:00	E01020316	West Devon 007D	26608	9	28618	9	28989	9	32162	10	25969	8	31763	10
{9B361206-17C6-1904-E053-6B04A8C0EEB5}	PL20 6JJ	200000	D	N	F	2019-11-29 00:00	E01020317	West Devon 006A	20801	7	24320	8	19297	6	30798	10	19355	6	22971	7
{9B361206-17C7-1904-E053-6B04A8C0EEB5}	TQ3 2LJ	240000	D	N	F	2019-12-09 00:00	E01015203	Torbay 012B	21635	7	21899	7	15994	5	25167	8	14966	5	19150	6
{9B361206-17C8-1904-E053-6B04A8C0EEB5}	EX4 6RP	126000	F	N	L	2019-11-20 00:00	E01020019	Exeter 004B	27981	9	31072	10	32691	10	27095	9	26357	9	28409	9
{9B361206-17C9-1904-E053-6B04A8C0EEB5}	PL21 9FZ	232000	S	Y	F	2019-07-04 00:00	E01020167	South Hams 005G	32466	10	31343	10	26453	9	31703	10	27317	9	29951	10
{9B361206-17CA-1904-E053-6B04A8C0EEB5}	EX12 2FH	199995	F	Y	L	2019-06-28 00:00	E01019947	East Devon 010B	15548	5	12568	4	12918	4	21100	7	16557	6	14891	5
{9B361206-17CB-1904-E053-6B04A8C0EEB5}	PL9 8GJ	255000	S	Y	F	2019-10-21 00:00	E01020187	South Hams 009D	19157	6	17077	6	12165	4	26414	9	21098	7	23777	8
{9B361206-17CC-1904-E053-6B04A8C0EEB5}	PL21 9FZ	260000	D	Y	F	2019-10-11 00:00	E01020167	South Hams 005G	32466	10	31343	10	26453	9	31703	10	27317	9	29951	10
{9B361206-17CD-1904-E053-6B04A8C0EEB5}	EX15 1UZ	110000	F	N	L	2019-10-18 00:00	E01020055	Mid Devon 007B	13938	5	12617	4	10767	4	23905	8	17267	6	5738	2
{9B361206-17CE-1904-E053-6B04A8C0EEB5}	EX22 6FQ	215000	T	Y	F	2019-10-18 00:00	E01020294	Torridge 008C	6946	3	6944	3	5974	2	26803	9	8991	3	4478	2
{9B361206-17CF-1904-E053-6B04A8C0EEB5}	EX1 3UX	399995	D	Y	F	2019-09-23 00:00	E01019893	East Devon 006C	20288	7	19052	6	19451	6	30421	10	28017	9	17851	6
{9B361206-17D0-1904-E053-6B04A8C0EEB5}	TQ9 5WY	470950	T	Y	F	2019-10-16 00:00	E01020184	South Hams 003E	14439	5	7265	3	8129	3	19941	7	20627	7	28951	9
{9B361206-17D1-1904-E053-6B04A8C0EEB5}	EX31 3GD	289995	D	Y	F	2019-10-16 00:00	E01020086	North Devon 012C	26013	8	24789	8	22745	7	18979	6	19586	6	20117	7
{9B361206-17D3-1904-E053-6B04A8C0EEB5}	EX31 3TW	453000	D	Y	F	2019-10-25 00:00	E01020106	North Devon 011B	19704	6	21352	7	17481	6	32722	10	12731	4	23766	8
{9B361206-17D4-1904-E053-6B04A8C0EEB5}	EX17 1FE	229995	S	Y	F	2019-03-29 00:00	E01020042	Mid Devon 011B	28993	9	26173	8	25620	8	27619	9	28636	9	17461	6
{9FF0D969-6884-11ED-E053-6C04A8C06383}	UB10 9NA	320000	F	N	L	2019-10-24 00:00	E01002513	Hillingdon 013D	21967	7	21007	7	16832	6	15420	5	22683	7	26677	9
{9FF0D969-6886-11ED-E053-6C04A8C06383}	W13 8RD	399000	F	N	L	2019-11-15 00:00	E01001222	Ealing 019A	12874	4	13108	4	16185	5	13668	5	20841	7	25621	8
{9B361206-17D7-1904-E053-6B04A8C0EEB5}	EX3 0FG	430000	S	Y	F	2019-10-25 00:00	E01020033	Exeter 015C	17593	6	12417	4	11876	4	17951	6	20467	7	20861	7
{9FF0D969-6888-11ED-E053-6C04A8C06383}	HA2 6BU	275000	F	N	L	2019-04-05 00:00	E01002161	Harrow 021C	19247	6	11499	4	18084	6	21803	7	27275	9	29498	9
{9B361206-17D9-1904-E053-6B04A8C0EEB5}	TQ9 6GU	360000	S	Y	F	2019-04-18 00:00	E01020181	South Hams 003B	17792	6	11145	4	10032	4	26856	9	15400	5	19881	7
{9B361206-17DA-1904-E053-6B04A8C0EEB5}	TQ1 4NW	350000	F	Y	L	2019-10-31 00:00	E01015239	Torbay 002D	5045	2	3574	2	2769	1	14742	5	3736	2	13841	5
{9B361206-17DB-1904-E053-6B04A8C0EEB5}	TQ9 7FN	365000	D	Y	F	2019-10-29 00:00	E01020188	South Hams 004D	17489	6	23907	8	25303	8	29674	10	28820	9	28651	9
{9B361206-17DC-1904-E053-6B04A8C0EEB5}	TQ1 3LD	500000	F	Y	L	2019-10-31 00:00	E01015236	Torbay 002A	11715	4	14486	5	9116	3	5638	2	13778	5	16132	5
{9B361206-17DD-1904-E053-6B04A8C0EEB5}	EX2 7NQ	354950	D	Y	F	2019-09-27 00:00	E01020033	Exeter 015C	17593	6	12417	4	11876	4	17951	6	20467	7	20861	7
{9FF0D969-6894-11ED-E053-6C04A8C06383}	W3 7UN	220000	F	N	L	2019-07-02 00:00	E01001245	Ealing 024F	18507	6	16403	5	22559	7	13345	5	24008	8	26961	9
{9B361206-17DF-1904-E053-6B04A8C0EEB5}	TQ7 2FA	195000	T	N	F	2019-10-03 00:00	E01020178	South Hams 011C	19888	7	24483	8	23902	8	32446	10	27927	9	24866	8
{9B361206-17E1-1904-E053-6B04A8C0EEB5}	TQ9 6GR	375000	S	Y	F	2019-10-31 00:00	E01020181	South Hams 003B	17792	6	11145	4	10032	4	26856	9	15400	5	19881	7
{9B361206-17E2-1904-E053-6B04A8C0EEB5}	EX31 3UG	330000	D	Y	F	2019-10-18 00:00	E01020105	North Devon 011A	22666	7	19686	6	17996	6	29187	9	15816	5	14395	5
{9B361206-275C-1904-E053-6B04A8C0EEB5}	N8 0SG	285000	F	N	L	2019-11-22 00:00	E01002003	Haringey 023C	5261	2	6416	2	9560	3	2282	1	12153	4	8164	3
{9B361206-275D-1904-E053-6B04A8C0EEB5}	E1W 2JF	630000	F	N	L	2019-09-06 00:00	E01004292	Tower Hamlets 026A	27385	9	27476	9	31829	10	16173	5	23286	8	29342	9
{9B361206-275E-1904-E053-6B04A8C0EEB5}	E11 2JU	1185000	S	N	F	2019-09-24 00:00	E01003796	Redbridge 018D	25148	8	25034	8	28543	9	10846	4	31375	10	30118	10
{9B361206-275F-1904-E053-6B04A8C0EEB5}	E17 4PL	575000	T	N	F	2019-11-29 00:00	E01004347	Waltham Forest 011C	18452	6	16302	5	22673	7	13403	5	25222	8	23465	8
{9B361206-2760-1904-E053-6B04A8C0EEB5}	N9 7PZ	196000	F	N	L	2019-12-04 00:00	E01001480	Enfield 024D	7739	3	7133	3	10874	4	11738	4	15576	5	13809	5

Checking for missing values

Before purely exploring the data and visualize what’s inside of it, we need to check for missing values in the data. I decided to do this check only after the joining of the tables because deleting values before wouldn’t have brought anything.

Missing values:

	missing	%
Unique_transaction_code	0	0
Postcode	0	0
Price	0	0
Housing_type	0	0
New_or_old	0	0
Freehold_Leasehold	0	0
Date	0	0
LSOA_code	0	0
LSOA_name	0	0
IMD_rank	0	0
IMD_decile	0	0
Income_rank	0	0
Income_decile	0	0
Employment_rank	0	0
Employment_decile	0	0
Crime_rank	0	0
Crime_decile	0	0
Health_Deprivation_rank	0	0
Health_Deprivation_decile	0	0
Skill_rank	0	0
Skill_decile	0	0

As we can see and as I was expecting, there are no missing values inside of the dataset, this is mainly due to the fact that during matching we had to have a valid LSOA code in England that would make us able to join the IMD information, this asked to filter for code starting by “E” and therefore eliminating NAs.

References

Price paid data : https://www.gov.uk/government/statistical-data-sets/price-paid-data-downloads#yearly-file Contains HM Land Registry data © Crown copyright and database right 2020. This data is licensed under the Open Government Licence v3.0.

IMD data (table2) : https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019 Contains public sector information licensed under the Open Government Licence v3.0.

Postcodes Data: https://www.doogal.co.uk/UKPostcodes.php Contains OS data © Crown copyright and database rights 2020 Contains Royal Mail data © Royal Mail copyright and database rights 2020 Contains National Statistics data © Crown copyright and database rights 2020 Contains data from Wikipedia covered by the Creative Commons license

Exploratory data analysis

In this section we will import the cleaned data and use it to start exploring the dataset and visualizing the information inside of it.

Exploration of the table

We are now going to look a bit more at the prices in details to see how they are in the data, the mean and max values and other statistical values that can be interesting to explore and usefull to to answer the research questions:

Prices statistical values

In this section we will explore the different statistical values of the price such as the mean, the max, the min, the median and the quantiles:

To do so, we are going to summarise the table around the price and creating a whole new one containing only the newly calculated values.

Min Price	1st quantile	Median	Mean	3rd Quantile	Max
1	152000	238000	353511	365000	411500000

Now let’s have a look at the density plot of the prices:
As we can see drawing the plot without limits does not help so we are going to draw it with limit on the x axis set to 10’000 and 3 millions. I have set those numbers in this way because in big cities you can find small housing for 20’000 therefore in smaller ones it might be possible to find some around 10’000. The 3 millions was set this way because you still find plenty of housing in London or other large cities around 1 to 2 millions but when you reach higher numbers those often comes with some more luxurious feature and are therefore “Prestige” housing which are on an other class.

This brings quite a lot of information for the rest of the project, in fact we have some extreme values in the dataset and those could well influence a lot our results and make the analysis way harder. In fact, the price of 411’500’000 is really high and therefore might change the results, it is needed to take this into account and extremes might need to be either aligned on a certain level or simply removed to make the analysis readable. The other strange and interesting point is the value of 1, it seems quite odd to have some real estate property costing only 1 pound, we do have to check how many small values are in the dataset to take them into account too.

We can see that we have 4296 housings over 3 millions which represent 0.46% of the complete table and 4097 housings under 10 thousands which represent 0.439% of the complete table.

In order to do a good analysis of the overall market we could maybe remove those values to do the regressions since those do not really reflect the “normal” market but extreme ones such as the most luxurious one which is cannot be compared from places to places since it’s mostly unique.

Before looking further let’s just have a look at the distribution of the sales of housing over 3 millions and under 10’000:

As we can see, the housing priced over 3 millions have the same type of distribution as when we take the overall dataset, there is nothing to really take out of this but it was important to check for pattern into this data too

While for the ones prices under 10’000 we can see that many are around 1000, to be honest I don’t really see what kind of property could be sold at that price, maybe those are rural parking spots but it is quite hard to know. the distribution is quite even and does not follow a precise rule.

Differences between new and old constructions

We will now check if there is a difference inside of the dataset which could help to explain some things later in between new and old buildings.
First, let’s have a look at the prices and their density:

New or old	Mean Price	Median Price
N	354741	230000
Y	345390	285000

To better see the difference let’s look at both by comparing them via boxplots:

This is quite interesting too, we can see that in general by looking at the median prices, the newly builded housing cost more than the old one but it seems that the extremes are more often present in the old buildings. This could be explained by the fact that a lot of “Prestige” Real estate is old and therefore the mean is further from the median compared to the newly built housing. An other point is that London is an old city and one of the costliest in the world it is therefore logic that a lot of old building sales could occur there and making this trend.

Before continuing on the prices, let’s just have a look at the distribution of the new and old housings on the market:

New or old	Quantity	Proportion
N	811269	0.869
Y	122834	0.131

As we can see, there are way more old houses sold on the market than new ones which is quite logic since a lot of the territory is already built and therefore it would be odd to find more new buildings than old with such a space limit.

To check the prices a bit more let’s have a look at the details, we have 229 newly built housing that sold for over 3 millions which represent 5.331% of all the housings over that price so we therefore have 4067 old housings sold over 3 millions representing the other 94.669%.

As we can see, the assumption made right before is confirmed as 94.669% of the buildings costing more than 3 millions are not newly built ones. let’s now check where those old buildings are:

LSOA name	Amount
Kensington and Chelsea 015C	81
City of London 001F	41
Westminster 018D	28
Westminster 016D	26
Westminster 013E	23
Westminster 019E	20
Westminster 018C	19
Westminster 019A	18
Westminster 019C	17
County Durham 063B	15
Westminster 011E	15
Bristol 032B	14
Westminster 018B	14
Kensington and Chelsea 018E	13
Westminster 019F	13
Camden 028B	12
Kensington and Chelsea 011A	12
Kensington and Chelsea 012D	12
Westminster 018A	12
Westminster 019D	12
Ealing 006A	11
Hackney 027G	11
Westminster 020A	11
Barnet 033B	10
Camden 021B	10
Kensington and Chelsea 007E	10
Kensington and Chelsea 018A	10
Westminster 011B	10
Westminster 011C	10
Camden 002E	9
City of London 001G	9
Kensington and Chelsea 008B	9
Kensington and Chelsea 012A	9
Kensington and Chelsea 012B	9
Kensington and Chelsea 012C	9
Kensington and Chelsea 018B	9
Kensington and Chelsea 019C	9
West Berkshire 011F	9
Westminster 011A	9
Westminster 013D	9
Camden 017D	8
Islington 022D	8
Islington 022H	8
Kensington and Chelsea 007B	8
Kensington and Chelsea 012E	8
Kensington and Chelsea 020B	8
Leeds 111A	8
Richmond upon Thames 003B	8
Southwark 018B	8
Westminster 013B	8
Westminster 014A	8
Westminster 014B	8
Westminster 015A	8
Wigan 006A	8
Birmingham 138A	7
Bristol 054C	7
Camden 027B	7
Eastleigh 013D	7
Kensington and Chelsea 008A	7
Kensington and Chelsea 009D	7
Kensington and Chelsea 010C	7
Kingston upon Thames 009C	7
Manchester 054C	7
Merton 002A	7
Runnymede 005D	7
Sefton 004G	7
Southampton 023B	7
Sutton 012D	7
Birmingham 033F	6
Camden 018C	6
Camden 026B	6
Camden 028C	6
Elmbridge 018B	6
Hammersmith and Fulham 010D	6
Kensington and Chelsea 011E	6
Kensington and Chelsea 013A	6
Kensington and Chelsea 014D	6
Kensington and Chelsea 017E	6
Luton 021C	6
Manchester 055B	6
Milton Keynes 014F	6
Tower Hamlets 018D	6
Trafford 002E	6
Westminster 001D	6
Westminster 003C	6
Westminster 013F	6
Wiltshire 042D	6
Windsor and Maidenhead 018A	6
Woking 008A	6
Camden 002A	5
Camden 004A	5
Camden 021A	5
Crawley 001C	5
Croydon 028D	5
Elmbridge 016A	5
Elmbridge 018D	5
Hammersmith and Fulham 020E	5
Haringey 034C	5
Havant 005D	5
Islington 013D	5
Kensington and Chelsea 006E	5
Kensington and Chelsea 010D	5
Kensington and Chelsea 016B	5
Kensington and Chelsea 016C	5
Kensington and Chelsea 016E	5
Kensington and Chelsea 018C	5
Kensington and Chelsea 018D	5
Kensington and Chelsea 019D	5
Kensington and Chelsea 019E	5
Leeds 111B	5
Manchester 052E	5
Merton 001C	5
Merton 002D	5
Northampton 028D	5
Nottingham 039B	5
Southwark 018C	5
Wandsworth 015E	5
Wandsworth 031C	5
Westminster 002A	5
Westminster 008C	5
Westminster 017B	5
Westminster 019B	5
Westminster 020C	5
Westminster 023C	5
York 013A	5
Ashfield 010A	4
Bath and North East Somerset 007A	4
Brent 027E	4
Brent 032C	4
Brighton and Hove 027G	4
Camden 002B	4
Camden 004D	4
Camden 012E	4
Camden 018E	4
Camden 022E	4
Camden 027D	4
City of London 001E	4
Coventry 031C	4
Crawley 004C	4
Ealing 034B	4
Elmbridge 013C	4
Elmbridge 016B	4
Exeter 003E	4
Hackney 014B	4
Hammersmith and Fulham 023C	4
Harborough 006D	4
Haringey 030B	4
Harlow 003E	4
Havant 014F	4
Islington 004B	4
Islington 023D	4
Kensington and Chelsea 004C	4
Kensington and Chelsea 006A	4
Kensington and Chelsea 006B	4
Kensington and Chelsea 006C	4
Kensington and Chelsea 006D	4
Kensington and Chelsea 007A	4
Kensington and Chelsea 007D	4
Kensington and Chelsea 008C	4
Kensington and Chelsea 008D	4
Kensington and Chelsea 009A	4
Kensington and Chelsea 010E	4
Kensington and Chelsea 011C	4
Kensington and Chelsea 013C	4
Kingston upon Hull 029E	4
Newcastle upon Tyne 018E	4
Newham 013H	4
Oxford 003D	4
Portsmouth 016B	4
Richmond upon Thames 008B	4
Richmond upon Thames 012C	4
Rotherham 017B	4
Runnymede 005A	4
Sheffield 073A	4
South Bucks 001A	4
South Bucks 001B	4
Southampton 022A	4
Southwark 002B	4
Southwark 002C	4
St Albans 012B	4
Thurrock 015C	4
Tower Hamlets 018C	4
Tower Hamlets 021F	4
Tunbridge Wells 008A	4
Watford 011E	4
West Dorset 011B	4
Westminster 001C	4
Westminster 002B	4
Westminster 002C	4
Westminster 008D	4
Westminster 014D	4
Westminster 017F	4
Westminster 023B	4
Windsor and Maidenhead 018B	4
Adur 005C	3
Barnet 007C	3
Barnet 035E	3
Barnet 038B	3
Barnet 039B	3
Basildon 015C	3
Bassetlaw 014E	3
Birmingham 037A	3
Bolton 022B	3
Bracknell Forest 005B	3
Brent 011A	3
Brent 029A	3
Bristol 041D	3
Broxbourne 002D	3
Camden 004B	3
Camden 004E	3
Camden 008C	3
Camden 012C	3
Camden 017C	3
Camden 023C	3
Camden 024B	3
Chelmsford 010F	3
Cheltenham 009G	3
Cheshire East 011A	3
Cheshire West and Chester 017C	3
Cheshire West and Chester 018B	3
Cornwall 007E	3
Dacorum 013B	3
Ealing 015D	3
Eastbourne 010C	3
Elmbridge 014D	3
Elmbridge 014F	3
Exeter 011G	3
Guildford 013E	3
Guildford 015A	3
Hackney 026C	3
Hackney 027F	3
Hammersmith and Fulham 001D	3
Hammersmith and Fulham 020C	3
Hammersmith and Fulham 024B	3
Haringey 030C	3
Harrow 023C	3
Havant 014A	3
Hillingdon 026D	3
Islington 005B	3
Islington 023E	3
Kensington and Chelsea 004D	3
Kensington and Chelsea 008E	3
Kensington and Chelsea 010A	3
Kensington and Chelsea 010B	3
Kensington and Chelsea 014A	3
Kensington and Chelsea 019B	3
Kensington and Chelsea 020A	3
Kingston upon Thames 002A	3
Lambeth 003E	3
Leicester 041A	3
Leicester 041C	3
Lewisham 029A	3
Lichfield 004E	3
Manchester 057C	3
Merton 004E	3
Merton 010A	3
Merton 012A	3
Newcastle upon Tyne 024C	3
Newcastle upon Tyne 024G	3
Newham 033B	3
Northampton 024C	3
Oxford 008A	3
Oxford 015C	3
Peterborough 021F	3
Redbridge 030G	3
Reigate and Banstead 012D	3
Richmond upon Thames 001D	3
Richmond upon Thames 006A	3
Richmond upon Thames 008A	3
Richmond upon Thames 008D	3
Richmond upon Thames 012A	3
Salford 028G	3
Sevenoaks 012A	3
Sheffield 074C	3
Sheffield 075G	3
Slough 007F	3
Slough 009B	3
South Bucks 002D	3
South Gloucestershire 005A	3
South Gloucestershire 017B	3
South Gloucestershire 017F	3
South Gloucestershire 019D	3
Southampton 021C	3
Southampton 023A	3
Southwark 034D	3
Staffordshire Moorlands 010B	3
Stevenage 008D	3
Stockton-on-Tees 014C	3
Stockton-on-Tees 014E	3
Stratford-on-Avon 009B	3
Swindon 010B	3
Swindon 019E	3
Taunton Deane 006D	3
Taunton Deane 007F	3
Tewkesbury 001E	3
Tower Hamlets 004E	3
Tower Hamlets 021D	3
Trafford 028D	3
Wandsworth 001D	3
Wandsworth 011A	3
Warrington 014A	3
Welwyn Hatfield 006C	3
West Berkshire 019A	3
Westminster 001A	3
Westminster 007B	3
Westminster 012D	3
Westminster 013A	3
Westminster 014G	3
Westminster 015B	3
Westminster 017C	3
Westminster 020E	3
Wigan 013B	3
Winchester 007C	3
Winchester 013F	3
Woking 008E	3
Wokingham 006A	3
Wycombe 001B	3
Wycombe 007D	3
Wycombe 015D	3
Amber Valley 015B	2
Barking and Dagenham 019E	2
Barking and Dagenham 021E	2
Barking and Dagenham 022C	2
Barnet 005B	2
Barnet 012E	2
Barnet 032B	2
Barnsley 006C	2
Bath and North East Somerset 004C	2
Bath and North East Somerset 012F	2
Bedford 018D	2
Birmingham 075D	2
Birmingham 079F	2
Birmingham 135C	2
Blaby 013B	2
Bournemouth 017A	2
Bournemouth 021A	2
Bracknell Forest 001C	2
Bracknell Forest 004D	2
Bradford 002D	2
Bradford 020E	2
Bradford 057E	2
Brent 030A	2
Brent 032B	2
Brentwood 007A	2
Brentwood 008D	2
Brighton and Hove 014C	2
Brighton and Hove 027C	2
Brighton and Hove 031A	2
Bristol 014D	2
Bristol 032C	2
Bristol 032E	2
Bristol 054B	2
Bristol 055C	2
Camden 001E	2
Camden 002D	2
Camden 006D	2
Camden 008B	2
Camden 008D	2
Camden 008E	2
Camden 011B	2
Camden 011D	2
Camden 014B	2
Camden 016D	2
Camden 018D	2
Camden 023B	2
Camden 026A	2
Camden 027A	2
Canterbury 014D	2
Castle Point 002E	2
Central Bedfordshire 013C	2
Central Bedfordshire 026D	2
Central Bedfordshire 027C	2
Charnwood 017B	2
Charnwood 017C	2
Chelmsford 014A	2
Cheltenham 008C	2
Cherwell 009C	2
Cheshire East 007E	2
Cheshire East 038D	2
Cheshire West and Chester 034A	2
Cheshire West and Chester 046A	2
Chichester 001A	2
Chichester 003A	2
Chichester 005A	2
Chichester 012C	2
Chichester 013G	2
City of London 001B	2
Colchester 004D	2
Cotswold 009B	2
Coventry 025C	2
Crawley 004A	2
Crawley 008D	2
Croydon 027C	2
Croydon 035C	2
Dacorum 013A	2
Derby 014B	2
Dudley 022C	2
East Dorset 008C	2
East Hampshire 016A	2
East Hertfordshire 014A	2
East Northamptonshire 008C	2
East Riding of Yorkshire 008B	2
Elmbridge 012D	2
Elmbridge 013B	2
Elmbridge 015B	2
Elmbridge 016D	2
Elmbridge 017E	2
Enfield 003B	2
Enfield 010A	2
Enfield 014A	2
Enfield 029B	2
Epping Forest 003C	2
Epping Forest 009A	2
Epping Forest 016B	2
Fareham 002C	2
Fareham 008A	2
Forest Heath 006C	2
Greenwich 038C	2
Hackney 025C	2
Halton 009A	2
Hammersmith and Fulham 008C	2
Hammersmith and Fulham 008D	2
Hammersmith and Fulham 009C	2
Hammersmith and Fulham 011A	2
Hammersmith and Fulham 011D	2
Hammersmith and Fulham 012F	2
Hammersmith and Fulham 013C	2
Hammersmith and Fulham 018B	2
Hammersmith and Fulham 021F	2
Hammersmith and Fulham 024A	2
Haringey 014D	2
Harrow 020B	2
Harrow 027D	2
Hart 008E	2
Havering 013C	2
Havering 026D	2
Hillingdon 010E	2
Hillingdon 016F	2
Hillingdon 022F	2
Hillingdon 030E	2
Hillingdon 032C	2
Hillingdon 033A	2
Hounslow 006D	2
Hounslow 008D	2
Huntingdonshire 016F	2
Ipswich 014E	2
Islington 003A	2
Islington 017C	2
Islington 020C	2
Islington 021B	2
Islington 022F	2
Islington 022G	2
Kensington and Chelsea 004A	2
Kensington and Chelsea 005B	2
Kensington and Chelsea 007C	2
Kensington and Chelsea 009B	2
Kensington and Chelsea 011B	2
Kensington and Chelsea 013B	2
Kensington and Chelsea 013D	2
Kensington and Chelsea 015A	2
Kensington and Chelsea 016A	2
Kensington and Chelsea 019A	2
Kensington and Chelsea 020C	2
Kensington and Chelsea 021D	2
King’s Lynn and West Norfolk 007B	2
Kingston upon Thames 003C	2
Kingston upon Thames 009A	2
Kingston upon Thames 010C	2
Kirklees 005B	2
Kirklees 029D	2
Lambeth 004G	2
Lambeth 029A	2
Lambeth 036B	2
Leeds 063B	2
Leeds 073A	2
Leeds 082F	2
Leeds 097B	2
Leeds 106A	2
Lincoln 005A	2
Lincoln 006C	2
Liverpool 060C	2
Liverpool 060D	2
Liverpool 061C	2
Liverpool 062B	2
Maldon 004B	2
Malvern Hills 011A	2
Manchester 060A	2
Medway 015D	2
Mendip 001B	2
Merton 002C	2
Merton 004C	2
Merton 005A	2
Merton 009B	2
Merton 011E	2
Merton 022B	2
Mid Sussex 001E	2
Mid Sussex 007A	2
Mid Sussex 009E	2
Mid Sussex 016E	2
Middlesbrough 001G	2
Milton Keynes 009D	2
Milton Keynes 015B	2
Milton Keynes 017A	2
Milton Keynes 017F	2
Mole Valley 010C	2
New Forest 007D	2
Newcastle-under-Lyme 004E	2
Newcastle upon Tyne 023B	2
Newham 013G	2
Newham 027C	2
North Hertfordshire 006E	2
North Somerset 004A	2
North Tyneside 015A	2
North Warwickshire 004A	2
North West Leicestershire 003C	2
Northampton 021F	2
Northampton 025A	2
Northampton 029A	2
Nottingham 022D	2
Nuneaton and Bedworth 003E	2
Oxford 008E	2
Peterborough 014A	2
Peterborough 018B	2
Poole 018E	2
Preston 013G	2
Purbeck 006G	2
Reading 011F	2
Redbridge 032A	2
Redditch 005B	2
Reigate and Banstead 010A	2
Reigate and Banstead 015A	2
Ribble Valley 004D	2
Richmond upon Thames 002B	2
Richmond upon Thames 008C	2
Rochdale 021F	2
Rotherham 025A	2
Runnymede 002C	2
Runnymede 004C	2
Runnymede 007F	2
Rushcliffe 004A	2
Rushmoor 006C	2
Salford 030C	2
Sandwell 023G	2
Sedgemoor 009E	2
Sefton 014B	2
Sevenoaks 012B	2
Sheffield 007A	2
Sheffield 073D	2
Shropshire 003F	2
Shropshire 021C	2
Shropshire 030A	2
Slough 011B	2
Solihull 009A	2
Solihull 019A	2
Solihull 022D	2
Solihull 024D	2
Solihull 028F	2
South Bucks 003B	2
South Bucks 008D	2
South Cambridgeshire 016B	2
South Gloucestershire 005C	2
South Gloucestershire 018G	2
South Hams 012B	2
South Lakeland 001B	2
South Norfolk 002C	2
South Oxfordshire 019B	2
South Staffordshire 008B	2
Southampton 017D	2
Southampton 023D	2
Southampton 029E	2
Southampton 029H	2
Southend-on-Sea 010A	2
Southwark 002A	2
Southwark 003H	2
Southwark 003I	2
Southwark 007B	2
Southwark 009F	2
Southwark 017B	2
Southwark 033B	2
Southwark 033E	2
Stockton-on-Tees 014F	2
Stoke-on-Trent 015B	2
Stratford-on-Avon 004D	2
Stroud 001C	2
Stroud 002D	2
Sunderland 010A	2
Sunderland 013B	2
Surrey Heath 001B	2
Surrey Heath 008C	2
Swindon 008A	2
Test Valley 005G	2
Test Valley 008C	2
Test Valley 015A	2
Thanet 014A	2
Three Rivers 006E	2
Tonbridge and Malling 003C	2
Tonbridge and Malling 005A	2
Tower Hamlets 001C	2
Tower Hamlets 008D	2
Tower Hamlets 015B	2
Trafford 025B	2
Trafford 025C	2
Trafford 025E	2
Vale of White Horse 002F	2
Wakefield 013A	2
Wakefield 036D	2
Waltham Forest 022B	2
Wandsworth 002G	2
Wandsworth 002H	2
Wandsworth 010E	2
Wandsworth 011B	2
Wandsworth 011C	2
Wandsworth 019D	2
Wandsworth 020C	2
Wandsworth 024B	2
Wandsworth 029D	2
Warrington 003B	2
Warrington 009A	2
Warwick 001C	2
Warwick 013B	2
Watford 009C	2
Waverley 010A	2
Wealden 005B	2
West Berkshire 009C	2
West Berkshire 010C	2
West Devon 003A	2
West Lancashire 015B	2
West Oxfordshire 002D	2
West Oxfordshire 003A	2
West Oxfordshire 004G	2
Westminster 001B	2
Westminster 008A	2
Westminster 012A	2
Westminster 016A	2
Westminster 017E	2
Westminster 021C	2
Westminster 022B	2
Westminster 022C	2
Wigan 013C	2
Wiltshire 012C	2
Winchester 002A	2
Winchester 003E	2
Winchester 008D	2
Windsor and Maidenhead 005G	2
Windsor and Maidenhead 005H	2
Windsor and Maidenhead 007E	2
Windsor and Maidenhead 010B	2
Windsor and Maidenhead 018F	2
Woking 001D	2
Wokingham 010D	2
Wolverhampton 011B	2
Wolverhampton 020F	2
Worcester 008C	2
Worthing 011C	2
Wychavon 001D	2
Wycombe 021D	2
Wyre 009C	2
Wyre 010D	2
York 006D	2
York 013I	2
Adur 008A	1
Allerdale 002D	1
Amber Valley 010A	1
Arun 003E	1
Arun 010C	1
Ashfield 004B	1
Ashfield 004C	1
Ashfield 005C	1
Ashfield 009D	1
Ashford 004B	1
Ashford 005D	1
Ashford 007A	1
Ashford 007B	1
Aylesbury Vale 001C	1
Aylesbury Vale 001F	1
Aylesbury Vale 002B	1
Aylesbury Vale 006B	1
Aylesbury Vale 012D	1
Aylesbury Vale 015D	1
Aylesbury Vale 021F	1
Barking and Dagenham 018C	1
Barking and Dagenham 018E	1
Barking and Dagenham 020B	1
Barking and Dagenham 021C	1
Barking and Dagenham 023E	1
Barnet 001C	1
Barnet 001E	1
Barnet 004C	1
Barnet 006B	1
Barnet 007B	1
Barnet 007D	1
Barnet 008D	1
Barnet 015D	1
Barnet 015E	1
Barnet 016C	1
Barnet 019A	1
Barnet 022D	1
Barnet 023A	1
Barnet 033D	1
Barnet 033F	1
Barnet 034C	1
Barnet 036A	1
Barnet 036B	1
Barnet 038A	1
Barnet 038E	1
Barnet 039A	1
Barnet 041B	1
Basildon 008A	1
Basildon 011C	1
Basildon 012B	1
Basildon 014D	1
Basildon 015B	1
Basildon 017E	1
Basingstoke and Deane 003E	1
Basingstoke and Deane 008D	1
Basingstoke and Deane 011E	1
Basingstoke and Deane 014D	1
Basingstoke and Deane 016D	1
Basingstoke and Deane 016E	1
Basingstoke and Deane 017B	1
Basingstoke and Deane 020A	1
Basingstoke and Deane 020B	1
Bassetlaw 004C	1
Bassetlaw 009A	1
Bath and North East Somerset 003D	1
Bath and North East Somerset 005C	1
Bath and North East Somerset 007B	1
Bath and North East Somerset 007C	1
Bath and North East Somerset 007E	1
Bath and North East Somerset 012A	1
Bath and North East Somerset 016B	1
Bath and North East Somerset 027B	1
Bedford 007F	1
Bedford 012A	1
Bedford 019A	1
Bexley 003B	1
Bexley 004D	1
Bexley 007E	1
Bexley 008C	1
Bexley 019A	1
Bexley 019B	1
Bexley 028C	1
Birmingham 021A	1
Birmingham 021D	1
Birmingham 022C	1
Birmingham 025C	1
Birmingham 028D	1
Birmingham 037C	1
Birmingham 049E	1
Birmingham 050C	1
Birmingham 050F	1
Birmingham 069D	1
Birmingham 074B	1
Birmingham 081F	1
Birmingham 096G	1
Birmingham 134E	1
Birmingham 135A	1
Birmingham 135D	1
Birmingham 136A	1
Birmingham 136D	1
Birmingham 137B	1
Birmingham 137E	1
Birmingham 139A	1
Blaby 004D	1
Blackburn with Darwen 006C	1
Blackburn with Darwen 010B	1
Blackburn with Darwen 013A	1
Blackpool 013C	1
Bolsover 001A	1
Bolsover 001C	1
Bolsover 007E	1
Bolsover 010F	1
Bolton 016D	1
Bolton 016E	1
Bolton 016F	1
Bolton 022E	1
Bolton 031B	1
Bolton 032D	1
Bournemouth 002B	1
Bournemouth 002C	1
Bournemouth 004A	1
Bournemouth 019G	1
Bournemouth 023C	1
Bracknell Forest 001E	1
Bracknell Forest 002C	1
Bracknell Forest 006F	1
Bracknell Forest 008D	1
Bracknell Forest 012A	1
Bracknell Forest 015B	1
Bradford 004F	1
Bradford 004H	1
Bradford 005C	1
Bradford 015C	1
Bradford 027D	1
Bradford 032C	1
Bradford 035E	1
Bradford 038E	1
Braintree 001A	1
Braintree 002B	1
Braintree 009D	1
Braintree 009F	1
Braintree 010C	1
Braintree 018B	1
Breckland 007A	1
Brent 001C	1
Brent 011B	1
Brent 012B	1
Brent 013A	1
Brent 016A	1
Brent 017B	1
Brent 017C	1
Brent 020A	1
Brent 020B	1
Brent 027F	1
Brent 028A	1
Brentwood 004C	1
Brentwood 005A	1
Brentwood 005E	1
Brentwood 006D	1
Brentwood 007B	1
Brentwood 008C	1
Brentwood 009D	1
Brighton and Hove 001B	1
Brighton and Hove 007A	1
Brighton and Hove 008A	1
Brighton and Hove 013C	1
Brighton and Hove 015D	1
Brighton and Hove 016A	1
Brighton and Hove 016D	1
Brighton and Hove 019D	1
Brighton and Hove 020C	1
Brighton and Hove 020D	1
Brighton and Hove 025A	1
Brighton and Hove 027A	1
Brighton and Hove 027E	1
Brighton and Hove 028C	1
Brighton and Hove 028D	1
Brighton and Hove 028E	1
Brighton and Hove 030A	1
Brighton and Hove 032D	1
Bristol 001E	1
Bristol 010C	1
Bristol 015D	1
Bristol 019A	1
Bristol 026A	1
Bristol 029E	1
Bristol 030A	1
Bristol 030C	1
Bristol 032F	1
Bristol 039E	1
Bristol 043D	1
Bristol 054A	1
Bristol 056B	1
Broadland 004E	1
Broadland 011A	1
Broadland 016D	1
Bromley 009F	1
Bromley 018B	1
Bromley 018C	1
Bromley 023A	1
Bromley 024C	1
Bromley 033A	1
Bromley 037A	1
Bromsgrove 011A	1
Bromsgrove 013A	1
Broxbourne 003A	1
Broxbourne 003B	1
Broxbourne 013B	1
Broxbourne 013C	1
Broxtowe 001C	1
Broxtowe 003C	1
Broxtowe 012A	1
Broxtowe 012C	1
Bury 013B	1
Calderdale 005D	1
Calderdale 013E	1
Cambridge 001B	1
Cambridge 006A	1
Cambridge 008A	1
Cambridge 010E	1
Cambridge 012B	1
Camden 001C	1
Camden 002C	1
Camden 003B	1
Camden 003D	1
Camden 004C	1
Camden 006E	1
Camden 007E	1
Camden 009E	1
Camden 010A	1
Camden 010E	1
Camden 014A	1
Camden 014D	1
Camden 015A	1
Camden 015B	1
Camden 016A	1
Camden 018B	1
Camden 019A	1
Camden 019D	1
Camden 021D	1
Camden 024A	1
Camden 025A	1
Camden 025E	1
Camden 026D	1
Camden 027C	1
Camden 028D	1
Cannock Chase 013B	1
Canterbury 001A	1
Canterbury 002A	1
Canterbury 016D	1
Canterbury 020G	1
Carlisle 010B	1
Carlisle 011A	1
Castle Point 011B	1
Central Bedfordshire 006C	1
Central Bedfordshire 010A	1
Central Bedfordshire 011D	1
Central Bedfordshire 011E	1
Central Bedfordshire 017D	1
Central Bedfordshire 019C	1
Central Bedfordshire 028B	1
Charnwood 002A	1
Charnwood 014E	1
Charnwood 014F	1
Charnwood 016A	1
Chelmsford 001C	1
Chelmsford 005F	1
Chelmsford 008A	1
Chelmsford 010A	1
Chelmsford 010G	1
Cheltenham 003C	1
Cheltenham 003D	1
Cheltenham 011D	1
Cherwell 004A	1
Cherwell 004G	1
Cherwell 008A	1
Cherwell 010E	1
Cherwell 011F	1
Cherwell 015D	1
Cherwell 016A	1
Cheshire East 006A	1
Cheshire East 010C	1
Cheshire East 011B	1
Cheshire East 011C	1
Cheshire East 012D	1
Cheshire East 022A	1
Cheshire East 033A	1
Cheshire East 038C	1
Cheshire East 047C	1
Cheshire East 051D	1
Cheshire West and Chester 015E	1
Cheshire West and Chester 025A	1
Cheshire West and Chester 033E	1
Cheshire West and Chester 033F	1
Cheshire West and Chester 038A	1
Cheshire West and Chester 043F	1
Cheshire West and Chester 047B	1
Chesterfield 006A	1
Chesterfield 010F	1
Chichester 003C	1
Chichester 004A	1
Chichester 005F	1
Chichester 008C	1
Chichester 010D	1
Chichester 011C	1
Chichester 013E	1
Chiltern 001A	1
Chiltern 001D	1
Chiltern 008A	1
Chiltern 008D	1
Chiltern 010A	1
Chiltern 010D	1
Chiltern 013D	1
Chorley 006F	1
Chorley 012B	1
Christchurch 001D	1
Christchurch 002D	1
Christchurch 004B	1
Christchurch 004D	1
Christchurch 006D	1
Christchurch 007C	1
City of London 001A	1
Colchester 007D	1
Colchester 021C	1
Corby 003C	1
Cornwall 001A	1
Cornwall 008B	1
Cornwall 018A	1
Cornwall 019A	1
Cornwall 037A	1
Cornwall 041E	1
Cornwall 044C	1
Cornwall 052A	1
Cotswold 002A	1
Cotswold 002B	1
Cotswold 002C	1
Cotswold 003A	1
Cotswold 004B	1
Cotswold 004D	1
Cotswold 005A	1
Cotswold 009D	1
County Durham 016D	1
County Durham 017C	1
County Durham 022A	1
County Durham 023B	1
County Durham 030A	1
County Durham 030F	1
County Durham 033D	1
County Durham 035F	1
County Durham 042B	1
County Durham 058A	1
Coventry 009B	1
Coventry 011A	1
Coventry 018C	1
Coventry 020A	1
Coventry 020B	1
Coventry 021D	1
Coventry 024A	1
Coventry 024C	1
Coventry 028B	1
Coventry 036E	1
Craven 003C	1
Craven 007B	1
Crawley 003E	1
Crawley 007D	1
Croydon 008D	1
Croydon 011E	1
Croydon 019D	1
Croydon 022A	1
Croydon 027B	1
Croydon 028A	1
Croydon 036B	1
Croydon 037B	1
Croydon 037C	1
Dacorum 001A	1
Dacorum 006B	1
Dacorum 009A	1
Dacorum 015D	1
Dacorum 021C	1
Dacorum 021F	1
Dacorum 022B	1
Darlington 001E	1
Darlington 014A	1
Dartford 012B	1
Daventry 003A	1
Daventry 005A	1
Derby 016A	1
Derby 018F	1
Derby 018G	1
Derby 023B	1
Derbyshire Dales 001B	1
Derbyshire Dales 002D	1
Doncaster 003E	1
Doncaster 009B	1
Doncaster 015F	1
Doncaster 022E	1
Dover 004D	1
Dover 005C	1
Dover 008A	1
Dover 010E	1
Dudley 001D	1
Dudley 013A	1
Dudley 028B	1
Dudley 035A	1
Ealing 005B	1
Ealing 006B	1
Ealing 007C	1
Ealing 015E	1
Ealing 025E	1
Ealing 027B	1
Ealing 027E	1
Ealing 029E	1
Ealing 029F	1
Ealing 030D	1
Ealing 032E	1
Ealing 033E	1
Ealing 034C	1
Ealing 034D	1
Ealing 038A	1
East Devon 009C	1
East Dorset 005B	1
East Hampshire 002C	1
East Hampshire 007D	1
East Hampshire 008A	1
East Hampshire 011A	1
East Hampshire 012F	1
East Hampshire 016B	1
East Hertfordshire 003E	1
East Hertfordshire 005A	1
East Hertfordshire 007F	1
East Hertfordshire 010B	1
East Hertfordshire 013B	1
East Hertfordshire 014D	1
East Hertfordshire 017C	1
East Hertfordshire 017D	1
East Hertfordshire 017E	1
East Lindsey 003A	1
East Northamptonshire 005C	1
East Northamptonshire 008D	1
East Riding of Yorkshire 011B	1
East Riding of Yorkshire 020C	1
East Riding of Yorkshire 025B	1
East Riding of Yorkshire 031B	1
East Riding of Yorkshire 031C	1
East Riding of Yorkshire 034A	1
East Riding of Yorkshire 035A	1
East Staffordshire 003A	1
East Staffordshire 003C	1
East Staffordshire 013D	1
Eastbourne 001C	1
Eastbourne 013B	1
Eastleigh 002C	1
Eastleigh 003C	1
Eastleigh 003E	1
Eastleigh 010E	1
Eden 005A	1
Elmbridge 010C	1
Elmbridge 013A	1
Elmbridge 017C	1
Elmbridge 017F	1
Elmbridge 018A	1
Enfield 007A	1
Enfield 007E	1
Enfield 009D	1
Enfield 012F	1
Enfield 020C	1
Enfield 027B	1
Enfield 032C	1
Enfield 033F	1
Epping Forest 002A	1
Epping Forest 005C	1
Epping Forest 006B	1
Epping Forest 009B	1
Epping Forest 011C	1
Epping Forest 014B	1
Epsom and Ewell 007B	1
Epsom and Ewell 008B	1
Epsom and Ewell 009E	1
Exeter 004B	1
Exeter 006A	1
Exeter 008C	1
Exeter 011E	1
Exeter 013C	1
Exeter 014A	1
Exeter 014C	1
Exeter 014E	1
Fareham 001D	1
Fareham 002D	1
Fareham 002F	1
Fenland 003H	1
Fenland 006G	1
Forest Heath 006B	1
Forest of Dean 004C	1
Forest of Dean 007A	1
Fylde 003C	1
Fylde 006C	1
Fylde 009A	1
Fylde 009C	1
Gateshead 007D	1
Gateshead 014A	1
Gateshead 022A	1
Gateshead 025D	1
Gateshead 027C	1
Gedling 001D	1
Gedling 008C	1
Gloucester 002B	1
Gloucester 004B	1
Gloucester 004E	1
Gloucester 004F	1
Gloucester 005B	1
Gloucester 007G	1
Gloucester 009E	1
Gloucester 011B	1
Great Yarmouth 001E	1
Greenwich 002A	1
Greenwich 036B	1
Greenwich 038B	1
Guildford 001B	1
Guildford 003B	1
Guildford 004C	1
Guildford 005C	1
Guildford 012A	1
Guildford 013A	1
Guildford 013B	1
Guildford 013C	1
Guildford 016C	1
Guildford 016D	1
Guildford 018A	1
Hackney 002D	1
Hackney 004E	1
Hackney 009B	1
Hackney 009D	1
Hackney 010E	1
Hackney 021G	1
Hackney 023C	1
Hackney 023F	1
Hackney 026A	1
Hackney 027D	1
Hackney 027H	1
Hackney 027I	1
Hackney 028A	1
Halton 008B	1
Hambleton 004F	1
Hambleton 008D	1
Hambleton 009C	1
Hambleton 011C	1
Hammersmith and Fulham 001A	1
Hammersmith and Fulham 002D	1
Hammersmith and Fulham 007D	1
Hammersmith and Fulham 011C	1
Hammersmith and Fulham 014C	1
Hammersmith and Fulham 014D	1
Hammersmith and Fulham 017A	1
Hammersmith and Fulham 017D	1
Hammersmith and Fulham 017E	1
Hammersmith and Fulham 018C	1
Hammersmith and Fulham 020A	1
Hammersmith and Fulham 021C	1
Hammersmith and Fulham 021D	1
Hammersmith and Fulham 023F	1
Hammersmith and Fulham 024C	1
Hammersmith and Fulham 024D	1
Hammersmith and Fulham 025A	1
Hammersmith and Fulham 025C	1
Harborough 003C	1
Harborough 008A	1
Harborough 010B	1
Harborough 010C	1
Haringey 005A	1
Haringey 007C	1
Haringey 008D	1
Haringey 015A	1
Haringey 015D	1
Haringey 016B	1
Haringey 016C	1
Haringey 021A	1
Haringey 021D	1
Haringey 023C	1
Haringey 030A	1
Haringey 030D	1
Haringey 033B	1
Haringey 035B	1
Haringey 036D	1
Harlow 001D	1
Harlow 002B	1
Harrogate 002A	1
Harrogate 004E	1
Harrogate 011B	1
Harrogate 012B	1
Harrogate 014C	1
Harrogate 015E	1
Harrogate 016A	1
Harrogate 016B	1
Harrogate 016D	1
Harrow 001A	1
Harrow 005E	1
Harrow 007A	1
Harrow 013A	1
Harrow 013B	1
Harrow 025B	1
Harrow 025C	1
Harrow 029A	1
Hart 004A	1
Hart 004C	1
Hart 011D	1
Hartlepool 002E	1
Hartlepool 007D	1
Hastings 009B	1
Havant 003E	1
Havant 013F	1
Havering 001A	1
Havering 007A	1
Havering 009E	1
Havering 013E	1
Havering 015A	1
Havering 016C	1
Havering 017B	1
Herefordshire 005G	1
Herefordshire 009A	1
Herefordshire 018B	1
Herefordshire 021A	1
Herefordshire 022A	1
Herefordshire 023B	1
Herefordshire 023D	1
Hertsmere 003E	1
Hertsmere 004B	1
Hertsmere 005A	1
Hertsmere 005D	1
Hertsmere 009C	1
Hertsmere 010A	1
Hertsmere 010D	1
Hertsmere 013A	1
High Peak 002E	1
High Peak 013A	1
Hillingdon 001A	1
Hillingdon 001C	1
Hillingdon 003A	1
Hillingdon 006B	1
Hillingdon 013A	1
Hillingdon 013C	1
Hillingdon 015C	1
Hillingdon 015F	1
Hillingdon 020C	1
Hillingdon 033B	1
Hinckley and Bosworth 011A	1
Horsham 001D	1
Horsham 004A	1
Horsham 006C	1
Horsham 011B	1
Horsham 014E	1
Hounslow 003C	1
Hounslow 003G	1
Hounslow 005C	1
Hounslow 009B	1
Hounslow 013E	1
Hounslow 015E	1
Hounslow 017E	1
Hounslow 020A	1
Hounslow 021E	1
Huntingdonshire 019A	1
Huntingdonshire 021E	1
Hyndburn 003E	1
Hyndburn 006F	1
Ipswich 003A	1
Ipswich 004E	1
Ipswich 010B	1
Ipswich 011C	1
Ipswich 012B	1
Ipswich 014C	1
Ipswich 014F	1
Isle of Wight 001E	1
Isle of Wight 003D	1
Isle of Wight 009C	1
Islington 001D	1
Islington 003F	1
Islington 004E	1
Islington 007B	1
Islington 009C	1
Islington 010E	1
Islington 013B	1
Islington 013C	1
Islington 016A	1
Islington 016B	1
Islington 017A	1
Islington 019D	1
Islington 020E	1
Islington 021A	1
Islington 022E	1
Kensington and Chelsea 003A	1
Kensington and Chelsea 004E	1
Kensington and Chelsea 005A	1
Kensington and Chelsea 009E	1
Kensington and Chelsea 011D	1
Kensington and Chelsea 013E	1
Kensington and Chelsea 015B	1
Kensington and Chelsea 017C	1
Kensington and Chelsea 020D	1
Kensington and Chelsea 020E	1
Kensington and Chelsea 021A	1
Kensington and Chelsea 021E	1
Kettering 006A	1
King’s Lynn and West Norfolk 001D	1
Kingston upon Hull 020B	1
Kingston upon Hull 029F	1
Kingston upon Hull 030B	1
Kingston upon Thames 001A	1
Kingston upon Thames 002B	1
Kingston upon Thames 002D	1
Kingston upon Thames 003E	1
Kingston upon Thames 008B	1
Kingston upon Thames 011B	1
Kingston upon Thames 013B	1
Kingston upon Thames 013E	1
Kingston upon Thames 016E	1
Kingston upon Thames 017C	1
Kingston upon Thames 018E	1
Kirklees 046C	1
Kirklees 056A	1
Knowsley 005A	1
Knowsley 005E	1
Lambeth 002D	1
Lambeth 002E	1
Lambeth 004A	1
Lambeth 004F	1
Lambeth 006C	1
Lambeth 009C	1
Lambeth 010D	1
Lambeth 011B	1
Lambeth 012A	1
Lambeth 013B	1
Lambeth 013D	1
Lambeth 018E	1
Lambeth 019E	1
Lambeth 022B	1
Lambeth 025A	1
Lambeth 027A	1
Lambeth 028C	1
Lambeth 029C	1
Lambeth 032D	1
Lambeth 033A	1
Lambeth 036A	1
Lambeth 036C	1
Lambeth 036D	1
Lambeth 036E	1
Lancaster 006D	1
Leeds 010B	1
Leeds 016B	1
Leeds 023C	1
Leeds 034C	1
Leeds 034D	1
Leeds 044E	1
Leeds 045A	1
Leeds 045B	1
Leeds 082A	1
Leeds 083A	1
Leeds 087D	1
Leeds 090E	1
Leeds 091E	1
Leeds 093D	1
Leeds 102B	1
Leeds 104D	1
Leeds 111C	1
Leeds 111E	1
Leeds 112B	1
Leicester 008B	1
Leicester 009B	1
Leicester 016D	1
Leicester 038A	1
Leicester 040C	1
Leicester 041B	1
Leicester 041D	1
Lewes 001A	1
Lewes 002B	1
Lewes 002C	1
Lewes 005A	1
Lewes 008C	1
Lewisham 007E	1
Lewisham 008E	1
Lewisham 009B	1
Lewisham 013A	1
Lewisham 013B	1
Lewisham 018C	1
Lewisham 026C	1
Lewisham 027A	1
Lewisham 028B	1
Lichfield 005B	1
Lichfield 007D	1
Lincoln 005B	1
Lincoln 006B	1
Liverpool 001B	1
Liverpool 013C	1
Liverpool 028A	1
Liverpool 048B	1
Liverpool 060A	1
Liverpool 061B	1
Luton 003C	1
Luton 007E	1
Luton 011B	1
Luton 015D	1
Luton 018F	1
Luton 019B	1
Maidstone 001C	1
Maidstone 003E	1
Maidstone 004F	1
Maidstone 004G	1
Maidstone 006F	1
Maidstone 009B	1
Maidstone 015C	1
Maidstone 015D	1
Maidstone 015E	1
Maldon 002D	1
Malvern Hills 001B	1
Malvern Hills 003C	1
Malvern Hills 009A	1
Manchester 017A	1
Manchester 017F	1
Manchester 018B	1
Manchester 018D	1
Manchester 025C	1
Manchester 032C	1
Manchester 034C	1
Manchester 034F	1
Manchester 038D	1
Manchester 042B	1
Manchester 047A	1
Manchester 050C	1
Manchester 053D	1
Manchester 053E	1
Manchester 054A	1
Manchester 054E	1
Manchester 055A	1
Manchester 055C	1
Manchester 056B	1
Manchester 056C	1
Manchester 060B	1
Manchester 060C	1
Mansfield 008F	1
Medway 011A	1
Medway 024B	1
Medway 030B	1
Medway 030D	1
Medway 035C	1
Melton 001E	1
Mendip 005C	1
Mendip 007C	1
Mendip 010E	1
Mendip 012A	1
Merton 002B	1
Merton 003A	1
Merton 004A	1
Merton 009C	1
Merton 025D	1
Mid Devon 001A	1
Mid Suffolk 007B	1
Mid Suffolk 012D	1
Mid Sussex 002B	1
Mid Sussex 004E	1
Mid Sussex 009B	1
Mid Sussex 011B	1
Mid Sussex 014D	1
Mid Sussex 014F	1
Mid Sussex 016B	1
Middlesbrough 011A	1
Milton Keynes 007A	1
Milton Keynes 010D	1
Milton Keynes 013D	1
Milton Keynes 014E	1
Milton Keynes 017C	1
Milton Keynes 018E	1
Milton Keynes 019C	1
Milton Keynes 021C	1
Milton Keynes 022D	1
Milton Keynes 022E	1
Milton Keynes 023D	1
Milton Keynes 024A	1
Milton Keynes 024B	1
Milton Keynes 026B	1
Milton Keynes 030B	1
Milton Keynes 032B	1
Mole Valley 003D	1
Mole Valley 009B	1
Mole Valley 009C	1
Mole Valley 012D	1
New Forest 006B	1
New Forest 017B	1
Newark and Sherwood 005B	1
Newark and Sherwood 007B	1
Newark and Sherwood 010B	1
Newark and Sherwood 011C	1
Newark and Sherwood 012F	1
Newcastle-under-Lyme 012A	1
Newcastle-under-Lyme 016A	1
Newcastle upon Tyne 006C	1
Newcastle upon Tyne 014F	1
Newcastle upon Tyne 017E	1
Newcastle upon Tyne 022B	1
Newcastle upon Tyne 022H	1
Newcastle upon Tyne 023F	1
Newcastle upon Tyne 023H	1
Newcastle upon Tyne 024H	1
Newcastle upon Tyne 025B	1
Newcastle upon Tyne 026B	1
Newham 003D	1
Newham 005C	1
Newham 008A	1
Newham 010E	1
Newham 012B	1
Newham 013F	1
Newham 034J	1
Newham 035B	1
Newham 036D	1
Newham 037E	1
North Devon 002D	1
North Dorset 002A	1
North East Derbyshire 004D	1
North East Lincolnshire 014B	1
North Hertfordshire 002C	1
North Hertfordshire 006B	1
North Hertfordshire 006D	1
North Kesteven 006C	1
North Kesteven 009B	1
North Kesteven 011B	1
North Kesteven 014E	1
North Norfolk 005A	1
North Norfolk 005C	1
North Somerset 007A	1
North Somerset 009E	1
North Tyneside 002C	1
North Tyneside 006B	1
North Tyneside 007A	1
North Tyneside 016B	1
North Tyneside 019D	1
North West Leicestershire 002B	1
North West Leicestershire 010B	1
North West Leicestershire 013D	1
Northampton 002A	1
Northampton 005B	1
Northampton 008B	1
Northampton 011A	1
Northampton 018D	1
Northampton 028C	1
Northampton 029D	1
Northumberland 001B	1
Northumberland 003F	1
Northumberland 004C	1
Northumberland 005A	1
Northumberland 015B	1
Northumberland 015D	1
Northumberland 019B	1
Northumberland 032C	1
Northumberland 033B	1
Norwich 001A	1
Norwich 002A	1
Norwich 005H	1
Norwich 014C	1
Nottingham 012D	1
Nottingham 023D	1
Nottingham 023F	1
Nottingham 023G	1
Nottingham 027D	1
Nottingham 028G	1
Nottingham 031H	1
Nottingham 035F	1
Nottingham 039E	1
Nuneaton and Bedworth 008B	1
Nuneaton and Bedworth 008C	1
Nuneaton and Bedworth 011A	1
Nuneaton and Bedworth 015D	1
Nuneaton and Bedworth 018E	1
Oldham 015B	1
Oldham 028A	1
Oxford 001A	1
Oxford 003C	1
Oxford 009D	1
Oxford 013F	1
Oxford 016B	1
Peterborough 009A	1
Peterborough 013B	1
Peterborough 013D	1
Peterborough 013F	1
Peterborough 014C	1
Peterborough 022D	1
Peterborough 023E	1
Plymouth 005A	1
Plymouth 005B	1
Plymouth 007E	1
Plymouth 015D	1
Plymouth 019D	1
Plymouth 024A	1
Plymouth 027E	1
Plymouth 029E	1
Poole 006E	1
Poole 008B	1
Poole 011A	1
Poole 016A	1
Poole 017A	1
Poole 017E	1
Portsmouth 002C	1
Portsmouth 004C	1
Portsmouth 004D	1
Portsmouth 008B	1
Portsmouth 008C	1
Portsmouth 011C	1
Portsmouth 018D	1
Portsmouth 024C	1
Portsmouth 025B	1
Portsmouth 026A	1
Preston 001A	1
Preston 007E	1
Preston 010A	1
Preston 010D	1
Preston 013E	1
Preston 014A	1
Purbeck 003B	1
Reading 001C	1
Reading 002A	1
Reading 007C	1
Reading 011D	1
Reading 011G	1
Reading 011H	1
Reading 011I	1
Reading 013A	1
Reading 017E	1
Reading 018C	1
Redbridge 001E	1
Redbridge 002A	1
Redbridge 007C	1
Redbridge 013C	1
Redbridge 023A	1
Redbridge 030H	1
Redcar and Cleveland 001A	1
Redcar and Cleveland 001B	1
Redcar and Cleveland 003E	1
Redcar and Cleveland 018C	1
Redditch 001C	1
Redditch 007C	1
Reigate and Banstead 007A	1
Reigate and Banstead 011C	1
Reigate and Banstead 014B	1
Reigate and Banstead 015B	1
Ribble Valley 001C	1
Ribble Valley 003D	1
Ribble Valley 008E	1
Richmond upon Thames 001A	1
Richmond upon Thames 001B	1
Richmond upon Thames 002A	1
Richmond upon Thames 002E	1
Richmond upon Thames 002F	1
Richmond upon Thames 003C	1
Richmond upon Thames 003G	1
Richmond upon Thames 004D	1
Richmond upon Thames 006C	1
Richmond upon Thames 009D	1
Richmond upon Thames 011A	1
Richmond upon Thames 012D	1
Richmond upon Thames 018C	1
Richmond upon Thames 021A	1
Richmond upon Thames 021B	1
Richmond upon Thames 021C	1
Richmond upon Thames 022B	1
Rochdale 015E	1
Rochdale 018B	1
Rochdale 018E	1
Rossendale 004G	1
Rossendale 008C	1
Rother 002A	1
Rother 003E	1
Rother 007B	1
Rotherham 008D	1
Rotherham 028C	1
Rugby 001E	1
Rugby 012C	1
Runnymede 001A	1
Runnymede 006B	1
Runnymede 007C	1
Runnymede 008A	1
Runnymede 008C	1
Rushcliffe 005A	1
Rushcliffe 006C	1
Rushmoor 005B	1
Rushmoor 010E	1
Ryedale 002A	1
Ryedale 008E	1
Salford 008C	1
Salford 022G	1
Salford 028E	1
Salford 028H	1
Salford 030E	1
Sandwell 001C	1
Sandwell 013F	1
Sandwell 016E	1
Sandwell 027D	1
Scarborough 012E	1
Scarborough 014G	1
Sedgemoor 001E	1
Sedgemoor 002F	1
Sedgemoor 014F	1
Sefton 002B	1
Sefton 013B	1
Sefton 016A	1
Sefton 027A	1
Sefton 032C	1
Selby 004E	1
Sevenoaks 002D	1
Sevenoaks 003B	1
Sevenoaks 004B	1
Sevenoaks 012F	1
Sevenoaks 015C	1
Sheffield 005C	1
Sheffield 014E	1
Sheffield 017C	1
Sheffield 018A	1
Sheffield 022D	1
Sheffield 026A	1
Sheffield 027A	1
Sheffield 032E	1
Sheffield 036A	1
Sheffield 036E	1
Sheffield 040E	1
Sheffield 040F	1
Sheffield 050D	1
Sheffield 068E	1
Sheffield 074A	1
Shepway 014C	1
Shropshire 002C	1
Shropshire 005A	1
Shropshire 010D	1
Shropshire 015E	1
Shropshire 034A	1
Slough 003B	1
Slough 007D	1
Slough 009D	1
Slough 009F	1
Slough 009G	1
Slough 010C	1
Slough 013E	1
Slough 014D	1
Solihull 009B	1
Solihull 016B	1
Solihull 022E	1
Solihull 028E	1
Solihull 029D	1
South Bucks 004D	1
South Bucks 005D	1
South Bucks 006D	1
South Bucks 007A	1
South Bucks 008F	1
South Cambridgeshire 006C	1
South Cambridgeshire 007C	1
South Cambridgeshire 009A	1
South Cambridgeshire 012C	1
South Cambridgeshire 017C	1
South Cambridgeshire 017D	1
South Cambridgeshire 017E	1
South Cambridgeshire 017F	1
South Cambridgeshire 018E	1
South Cambridgeshire 020B	1
South Derbyshire 001C	1
South Derbyshire 001D	1
South Derbyshire 003D	1
South Derbyshire 009B	1
South Gloucestershire 009E	1
South Gloucestershire 011C	1
South Gloucestershire 011D	1
South Gloucestershire 011G	1
South Gloucestershire 021A	1
South Gloucestershire 022C	1
South Gloucestershire 028A	1
South Gloucestershire 029C	1
South Hams 004B	1
South Hams 005F	1
South Hams 008A	1
South Hams 009D	1
South Holland 004A	1
South Kesteven 008A	1
South Lakeland 001C	1
South Lakeland 007C	1
South Lakeland 012B	1
South Northamptonshire 001D	1
South Northamptonshire 005E	1
South Northamptonshire 011B	1
South Oxfordshire 006C	1
South Oxfordshire 009A	1
South Oxfordshire 017D	1
South Oxfordshire 018A	1
South Oxfordshire 018D	1
South Oxfordshire 019C	1
South Ribble 005A	1
South Ribble 013C	1
South Ribble 016D	1
South Somerset 001C	1
South Somerset 005B	1
South Somerset 005D	1
South Somerset 022A	1
South Somerset 022D	1
South Staffordshire 012C	1
South Staffordshire 013A	1
South Staffordshire 013B	1
South Tyneside 007B	1
South Tyneside 009A	1
South Tyneside 010B	1
Southampton 014D	1
Southampton 020A	1
Southampton 020B	1
Southampton 020D	1
Southampton 022B	1
Southampton 022F	1
Southampton 023C	1
Southampton 029F	1
Southend-on-Sea 002E	1
Southend-on-Sea 015B	1
Southwark 002D	1
Southwark 003E	1
Southwark 006F	1
Southwark 010E	1
Southwark 014F	1
Southwark 015A	1
Southwark 021D	1
Southwark 026D	1
Southwark 028A	1
Spelthorne 001A	1
Spelthorne 004A	1
Spelthorne 004C	1
Spelthorne 010C	1
St Albans 003A	1
St Albans 003C	1
St Albans 005B	1
St Albans 007B	1
St Albans 009B	1
St Albans 013C	1
St Albans 017D	1
St Edmundsbury 004C	1
St Edmundsbury 006A	1
St Edmundsbury 009C	1
St Edmundsbury 014E	1
St. Helens 004B	1
St. Helens 010B	1
St. Helens 014C	1
St. Helens 015D	1
St. Helens 019G	1
St. Helens 019J	1
Stafford 006C	1
Stafford 010B	1
Stafford 012B	1
Stevenage 002B	1
Stevenage 011D	1
Stockport 007C	1
Stockport 007D	1
Stockport 010E	1
Stockport 011B	1
Stockport 020D	1
Stockport 022A	1
Stockport 031D	1
Stockport 035D	1
Stockton-on-Tees 002E	1
Stockton-on-Tees 014G	1
Stoke-on-Trent 002D	1
Stoke-on-Trent 023D	1
Stoke-on-Trent 026D	1
Stoke-on-Trent 033A	1
Stratford-on-Avon 004E	1
Stratford-on-Avon 010E	1
Stratford-on-Avon 014A	1
Stroud 002A	1
Suffolk Coastal 007I	1
Suffolk Coastal 008B	1
Suffolk Coastal 011A	1
Suffolk Coastal 015A	1
Sunderland 007A	1
Sunderland 020F	1
Sunderland 026E	1
Sunderland 029C	1
Surrey Heath 001D	1
Surrey Heath 001E	1
Surrey Heath 001F	1
Surrey Heath 002B	1
Surrey Heath 002C	1
Surrey Heath 005E	1
Surrey Heath 008D	1
Surrey Heath 010A	1
Surrey Heath 012D	1
Sutton 011A	1
Sutton 018C	1
Sutton 019C	1
Sutton 022B	1
Sutton 024C	1
Swale 010E	1
Swale 013C	1
Swindon 005B	1
Swindon 008B	1
Swindon 009B	1
Swindon 012B	1
Swindon 012F	1
Swindon 014A	1
Swindon 014D	1
Swindon 017A	1
Swindon 023F	1
Swindon 028B	1
Tameside 002A	1
Tameside 013B	1
Tameside 016A	1
Tameside 020A	1
Tameside 030D	1
Tamworth 002A	1
Tandridge 002D	1
Tandridge 004D	1
Tandridge 012C	1
Taunton Deane 007D	1
Taunton Deane 009D	1
Taunton Deane 010B	1
Taunton Deane 011E	1
Taunton Deane 012A	1
Taunton Deane 014B	1
Teignbridge 001D	1
Teignbridge 002B	1
Teignbridge 003C	1
Teignbridge 010B	1
Telford and Wrekin 009A	1
Telford and Wrekin 023A	1
Tendring 008G	1
Tendring 013A	1
Tendring 014E	1
Tendring 018E	1
Test Valley 002A	1
Test Valley 003B	1
Test Valley 004E	1
Tewkesbury 001D	1
Tewkesbury 003B	1
Tewkesbury 003D	1
Tewkesbury 004A	1
Tewkesbury 006B	1
Thanet 002D	1
Thanet 008D	1
Thanet 011B	1
Thanet 011C	1
Thanet 012B	1
Three Rivers 011B	1
Three Rivers 011C	1
Three Rivers 012D	1
Thurrock 005A	1
Thurrock 013B	1
Thurrock 018A	1
Tonbridge and Malling 002G	1
Tonbridge and Malling 005E	1
Tonbridge and Malling 006B	1
Tonbridge and Malling 010A	1
Tonbridge and Malling 012D	1
Torbay 002A	1
Torbay 005C	1
Torbay 014A	1
Tower Hamlets 003C	1
Tower Hamlets 005C	1
Tower Hamlets 010F	1
Tower Hamlets 014A	1
Tower Hamlets 016A	1
Tower Hamlets 017B	1
Tower Hamlets 018A	1
Tower Hamlets 022D	1
Tower Hamlets 023C	1
Tower Hamlets 024A	1
Tower Hamlets 026B	1
Tower Hamlets 027A	1
Tower Hamlets 028A	1
Tower Hamlets 028I	1
Tower Hamlets 033B	1
Trafford 011D	1
Trafford 019A	1
Trafford 019B	1
Trafford 024C	1
Trafford 027B	1
Trafford 027C	1
Trafford 028A	1
Trafford 028C	1
Tunbridge Wells 003B	1
Tunbridge Wells 004B	1
Tunbridge Wells 004E	1
Tunbridge Wells 005D	1
Tunbridge Wells 006B	1
Tunbridge Wells 008B	1
Tunbridge Wells 008C	1
Tunbridge Wells 012D	1
Uttlesford 005A	1
Uttlesford 006B	1
Vale of White Horse 006H	1
Vale of White Horse 010C	1
Vale of White Horse 010D	1
Vale of White Horse 010E	1
Vale of White Horse 014B	1
Vale of White Horse 015B	1
Vale of White Horse 015D	1
Vale of White Horse 016E	1
Wakefield 005B	1
Wakefield 009D	1
Wakefield 012C	1
Wakefield 014A	1
Wakefield 015B	1
Wakefield 024A	1
Wakefield 028A	1
Wakefield 031D	1
Wakefield 038D	1
Walsall 027A	1
Walsall 038A	1
Waltham Forest 002B	1
Waltham Forest 004C	1
Waltham Forest 013D	1
Waltham Forest 014E	1
Waltham Forest 024C	1
Wandsworth 002B	1
Wandsworth 006D	1
Wandsworth 007D	1
Wandsworth 008E	1
Wandsworth 010A	1
Wandsworth 010B	1
Wandsworth 011E	1
Wandsworth 012A	1
Wandsworth 016A	1
Wandsworth 016D	1
Wandsworth 017A	1
Wandsworth 019A	1
Wandsworth 020B	1
Wandsworth 021B	1
Wandsworth 021E	1
Wandsworth 022D	1
Wandsworth 023D	1
Wandsworth 024D	1
Wandsworth 025A	1
Wandsworth 027A	1
Wandsworth 027E	1
Wandsworth 031D	1
Wandsworth 033D	1
Wandsworth 035A	1
Wandsworth 037C	1
Warrington 003C	1
Warrington 004C	1
Warrington 006E	1
Warrington 009B	1
Warrington 009C	1
Warrington 013B	1
Warrington 016A	1
Warrington 021C	1
Warrington 023C	1
Warrington 023E	1
Warrington 024A	1
Warwick 005B	1
Warwick 005G	1
Warwick 011H	1
Warwick 012A	1
Warwick 012E	1
Watford 005A	1
Watford 006D	1
Watford 009A	1
Watford 009D	1
Watford 012B	1
Waverley 001B	1
Waverley 004D	1
Waverley 007D	1
Waverley 011B	1
Waverley 012A	1
Waverley 012D	1
Waverley 015B	1
Waverley 015D	1
Waverley 015E	1
Waverley 018C	1
Waverley 018D	1
Wealden 001B	1
Wealden 014E	1
Wealden 016D	1
Wealden 018D	1
Wellingborough 003D	1
Wellingborough 005A	1
Wellingborough 007A	1
Welwyn Hatfield 001C	1
Welwyn Hatfield 007A	1
Welwyn Hatfield 015B	1
Welwyn Hatfield 016A	1
West Berkshire 001A	1
West Berkshire 002C	1
West Berkshire 005B	1
West Berkshire 006A	1
West Berkshire 009D	1
West Berkshire 011B	1
West Berkshire 013A	1
West Berkshire 019B	1
West Dorset 001B	1
West Dorset 004E	1
West Lancashire 004D	1
West Lancashire 011A	1
West Oxfordshire 002A	1
West Oxfordshire 003C	1
West Oxfordshire 010E	1
West Oxfordshire 011C	1
West Oxfordshire 012C	1
Westminster 003A	1
Westminster 003B	1
Westminster 003E	1
Westminster 005C	1
Westminster 006C	1
Westminster 007E	1
Westminster 007F	1
Westminster 008B	1
Westminster 009F	1
Westminster 009H	1
Westminster 009I	1
Westminster 011D	1
Westminster 012C	1
Westminster 014F	1
Westminster 015C	1
Westminster 015E	1
Westminster 016C	1
Westminster 017A	1
Westminster 020B	1
Westminster 021E	1
Westminster 023D	1
Westminster 023E	1
Weymouth and Portland 002B	1
Weymouth and Portland 003D	1
Wigan 013E	1
Wigan 017C	1
Wigan 019E	1
Wigan 021E	1
Wigan 024D	1
Wigan 026D	1
Wigan 027B	1
Wigan 031E	1
Wigan 036E	1
Wigan 038C	1
Wiltshire 007E	1
Wiltshire 007G	1
Wiltshire 011D	1
Wiltshire 012A	1
Wiltshire 012B	1
Wiltshire 019A	1
Wiltshire 022B	1
Wiltshire 022D	1
Wiltshire 023A	1
Wiltshire 023C	1
Wiltshire 024D	1
Wiltshire 025C	1
Wiltshire 026B	1
Wiltshire 048D	1
Wiltshire 050A	1
Wiltshire 058C	1
Wiltshire 062A	1
Winchester 004A	1
Winchester 004E	1
Winchester 005C	1
Winchester 006A	1
Winchester 006B	1
Winchester 006D	1
Winchester 009C	1
Winchester 011B	1
Winchester 012F	1
Winchester 013A	1
Winchester 013D	1
Winchester 014D	1
Windsor and Maidenhead 002B	1
Windsor and Maidenhead 002G	1
Windsor and Maidenhead 004E	1
Windsor and Maidenhead 005B	1
Windsor and Maidenhead 005D	1
Windsor and Maidenhead 009E	1
Windsor and Maidenhead 010A	1
Windsor and Maidenhead 011A	1
Windsor and Maidenhead 015A	1
Windsor and Maidenhead 017B	1
Windsor and Maidenhead 017D	1
Wirral 016A	1
Wirral 018D	1
Woking 003A	1
Woking 004E	1
Woking 006B	1
Woking 006C	1
Wokingham 001A	1
Wokingham 002E	1
Wokingham 006B	1
Wokingham 009C	1
Wokingham 011D	1
Wokingham 012H	1
Wokingham 013C	1
Wokingham 017B	1
Wolverhampton 001B	1
Wolverhampton 009B	1
Wolverhampton 012C	1
Wolverhampton 012D	1
Wolverhampton 018E	1
Wolverhampton 027A	1
Wolverhampton 032B	1
Wolverhampton 034A	1
Worcester 003A	1
Worcester 007C	1
Worcester 011E	1
Worcester 012A	1
Worthing 009A	1
Wychavon 007B	1
Wycombe 002A	1
Wycombe 003D	1
Wycombe 006B	1
Wycombe 015E	1
Wycombe 020B	1
Wycombe 023A	1
Wycombe 023B	1
Wycombe 024C	1
Wyre 007C	1
Wyre Forest 012E	1
York 003B	1
York 007B	1
York 011B	1
York 013C	1
York 013G	1

By browsing through the table we can see that a lost of the buildings are coming from the greater region of London (Westminster, chelsea, city of London, etc) but not only and some other regions still have a few housing that were sold for over 3 millions.

Difference in between housing types

We are now going to have a look at the different types of housing that we can find in the dataset, as like as for the new and old variable this could help to explain some of the results of the research questions.

Housing type	Mean price	Median price
D	420082	345000
F	304942	212500
O	1213602	268000
S	259309	215000
T	243095	183000

This is maybe one of the most interesting thing as of right now, we can see there that Semi-detached (S), Flats (F), and Terraced(T) housing follow the same logic and seem to be quite well distributed since the mean is more or less close to the median. Detached (D) housings are following the same logic but have, as it could be expected more pricey.

The key point here is the Other category which shows where it seems that we have most of the extremes, this could well be explained by the fact that this category might have the big apartments buildings inside of it which would explain the max value seem earlier of 411’500’000.

Just for the number, let’s check how many observations have a price over 3 millions for the other category and it’s proportion:

Unsurprisingly this category alone has 3050 representing 0.71% of the whole number of buildings over 3 millions which confirm in a way what was told before, there is sadly no data to be 100% sure about the fact that those are apartment buildings but the odds are high that this is the case.

Now, let’s check the distribution of the housign types in the new and old categries:

As we can see, the market is a bit different in what we build compare to what we have built until now, development of big cities push to mainly develop flats in them while people who are running away from those same cities want to have privacy and therefore ask for detached housing which leads to lower construction of semi-detached and Terraced housings.

Leasehold and freehold

In the dataset we have information about the way housing were bought, freehold meaning that the buyers owns the land and leasehold meaning that the buyer have the right from the landlord to live on his plot for a certain amount of time. Here his the table with the density plot and the distribution of them:

Freehold or Leasehold	Mean Price	Median Price
F	361321	250000
L	328158	193000

And their distribution in between the two categories:

Freehold or Leasehold	Quantity	Proportion
F	714124	0.765
L	219979	0.235

As we can clearly see, around three quarters of the properties are bought as freehold, and the last quarter as leasehold. Quite logically, in general freehold properties cost more than leasehold since the plot comes with the building itself. But what’s their distribution in terms on new and old?

As we can see, the proportion of leasehold is higher in the newly built housings, this may be due to the fact that the prices have increased since the 2008 crisis and to be able to sell more easily the buildings, the leasehold help decreasing the price and therefore reduce the price a little bit. And what about the types of housings?

Here we have the complete answer, most of the leasehold happens in the flats, meaning that the landlords decided to let someone build an apartment building on their plot while still keeping it, it is not uncommon since most of the old flats are the same. The key point is that the fact that the proportion of newly built homes as leasehold is higher that for old ones comes from what we are building today.

Even thought as we have seen earlier we build more detached houses than flats, the proportion is nearly the same while in the old building market the proportion of detached is quite higher, therefore this leads to a larger share of leasehold in the newly built market.

Evolution of the mean and median prices during the year

Just by curiosity, one interesting thing to explore is the evolution of the mean and median prices during the year which can be seen in the graph here:

As we can see, at least for monthly data, it does not seem to have any real trend on the evolution of prices during the year now let’s look at the evolution of the number of sales:

This time we have a bit more information, it seems that more sales, not a lot more but stil, are occurring in the second part of the year compared to the first part this could be explained by the fact that many people are either hard working around the beginning of the year to make the company statements or recovering from the winter holidays and therefore less interested into buying new houses.

But is this the same for both old and new housings, let’s find out:

As we can see here, it does not seem to have the same logic when looking at newly built buildings, those are quite better distributed compared to the old ones that still seems to be bought a bit more often at the end of the year. This may therefore be caused by fiscality purposes more than for delivering the housing to a client.

In the new buildings we just have 2 small peaks that are in june and december, the june one might be due to the fact that the good weather accelerate the delivery and the december one is certainly due to the will to deliver for the new year.

IMD decile and number of sales

One interesting thing to see would be the number of sales for each decile, we could assume instinctively that the less deprived regions are buying more than the most deprived since they should in some sort of way be “richer” let’s have a look at this:

IMD decile	Quantity
1	66573
2	76508
3	86452
4	93002
5	98857
6	104031
7	103297
8	105076
9	102228
10	98079

As we can see, the most deprived (on the left) are effectively the regions with the least amount of building bought, but what is interesting is that the least deprived places (on the right) are not the regions where most of the exchanges are made, we will see later in the analysis how the prices evolves but this could be one of the factor that is influencing in this way.

This result is quite unsurprising but at least gives good information about how the market is working.

Analysis

In this part we are going to start looking at the datas in order to answer the reasearch question and give the answer at the end.

1st question : “Are the housing prices linked to the the Employment, Criminality, Income and Health deprivation levels of the different geographical regions ?”

Here the objective is to have a look at different component from de deprivation index and their effect on the prices to see which ones have the most and the least effect.

Correlation matrix

#>                         Income_rank Employment_rank Crime_rank Health_Deprivation_rank
#> Income_rank                   1.000           0.941      0.627                   0.792
#> Employment_rank               0.941           1.000      0.572                   0.836
#> Crime_rank                    0.627           0.572      1.000                   0.588
#> Health_Deprivation_rank       0.792           0.836      0.588                   1.000

As we can see Employment and income are highly correlated, we will therefore only look at one of them in the following analysis. This analysis will be executed with the deciles and not the rank for a simple reason, that will reduce the x axis nd make the picture easier to look at.

Regression and coefficients

Before even showing any regression line, I have to say that I am only going to prin the line itself and will avoid bringing all the 900’000 points on each graphics to lower the calculation time and in any way, so many points would only make the graphic having a dark theme more than bringing any important information.

Income

We will first look at the Income , its regression and correlation information:

As we can see, at first sight we have a relationship which is positive, meaning that when the revenue rank or score increase, the Price of the housing increase too. it is a logical relatonship in the way that people have more money and therefore are ready to pay more to have a better home.

#> 
#>  Pearson's product-moment correlation
#> 
#> data:  Final_analysis_table$Price and Final_analysis_table$Income_decile
#> t = 48, df = 934101, p-value <2e-16
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  0.0472 0.0513
#> sample estimates:
#>    cor 
#> 0.0492

As we can see, the correlation is really low, explaining only 4% of the evolution but the p-value is really low meaning that it is still statistically significant. It is therefore not to throw but it could clearly not be used all alone to explain anything.

With this model we have a intercept of 174839 and a slope of 30596 by decile which is quite a lot when you think about it. Even though the intercept is still quite higher than the minimum price we ca find in the most deprived area by looking at the tables for the 2nd question.

Crime

Now let’s have a look at the same things but for the crime decile:

We have again a positive relationship but this time it seems to be flatter than before. It does have a link but it looks like this time it is even lower than what it was for the income. lets find out by looking at the correlation informations:

#> 
#>  Pearson's product-moment correlation
#> 
#> data:  Final_analysis_table$Price and Final_analysis_table$Crime_decile
#> t = 21, df = 934101, p-value <2e-16
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  0.0198 0.0239
#> sample estimates:
#>    cor 
#> 0.0218

Once again the correlation is low, this time even lower being around 2%, but again the p-value is extremely low therefore this is still statistically significant but could hardly be used alone to explain anything. Still lets check the slope and itnercept of this:

With this model we have a intercept of 279841 and a slope of 12980 by decile which is not that much this time, it looks like the relationship is more complex. In fact crimes are happening a lot in wealthy areas too and therefore the crime ranking will be quite different from the Income one. This could be explored further by maybe looking at which crime type has a link and which has not in further research.

Health

Let’s now check for the health levels :

We do have again a positive relationship which seems, visually at least to be quite similar to the one we had with the income. Let’s look once again at the correlation values:

#> 
#>  Pearson's product-moment correlation
#> 
#> data:  Final_analysis_table$Price and Final_analysis_table$Health_Deprivation_decile
#> t = 69, df = 934101, p-value <2e-16
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  0.0695 0.0736
#> sample estimates:
#>    cor 
#> 0.0716

This time the correlation is a bit higher, around 7% and the p-value still indicate a that this is statistically significant which is quite interesting.

With this model we have a intercept of 105956 and a slope of 43209. This time it is closer to the values we have in the reality in terms of minimas and maximas even though it is not really perfect either.

To conclude for this question, there is an effect for each of the ranking we looked about sadly the effect is not that big, the key point to take here is the fact that at least when we look at this dataset the p-value is extremely low, therefore even though we are not explaining a lot of the variation with each one of the variables those could be included inside a model with the volume and other classical aspect from housing to create some more precise models. But this should still be analyzed by potential further research.

2nd question : “Are the mean, median prices and overall price range in an area linked to the IMD?”

We can already see a trend here, the boxplot are slowly going to the right but let’s have a look at each individual value in a table to really see those numbers :

IMD decile	Minimum price	1st quantile	Median price	mean price	3rd quantile	Maximum price
1	100	75000	113000	166090	162500	56700000
2	100	104000	152000	252012	239950	95000000
3	1	122500	182000	318627	295000	276570000
4	100	140000	206000	319421	315000	145000000
5	100	159950	232000	345599	345000	315000000
6	100	172000	250000	371628	374000	262890000
7	100	181500	262995	399046	382500	337000000
8	1	192000	275000	401738	400000	139480000
9	100	210000	296000	407304	430000	103050000
10	1	250000	350000	456046	502500	411500000

Let’s just plot that and then we will speak about it, we are not going to put the min and the max in the plt since this is not bringing that much to the analysis.

As it is nicely shown in the graph, the less deprived an area is in general, the higher the price is, it is quite logic but I would have though that some values could have been way closer than what they are because even if people are quite poor you can find some wealthy investment in the same area but this is not even really shown in this result. We can see this logic a little bit by looking at the mean and the 3rd quantile, they cross each other and the 3rd quantile is higher than the mean only for the 3 last deciles meaning that in the other deciles, the extremes have more “power” and move the mean higher than in the less deprived areas.

If we really look at the prices in the table, we can see that in all columns in between the least an and the most deprived we have a factor of 3 to 5 times the price going for example from 160 thousands up to 500 thousands for the 3rd quantile which is really impressive. What is more, we can see that the 1st quantile of the least deprived ares is at 250 thousands while as I just said, the 3rd quantile of the most deprived area is at 160 thousands, meaning that most of the 25 cheapest percent of the least deprived area housings cost more than the 25% most expensive ones in the highly deprived areas.

To conclude for this question,I believe that we can really see a link between the IMD and the price of the housing in a region. It is, in the end something that is logic but I am quite surprised by the level of this link.

3rd question : “Is there a difference in the type of housings depending on the deprivation levels?”

In order to answer this question we need to visualize the type of housing sold by LSOA:

As we can clearly see d have differences in what is sold in the different IMD levels. It seems that most of the sales from the least deprived area are detached and semi-detached housings while in the most deprived ones we have a lot of flats and terraced housings.

This is interesting in the way that it explains part of the price difference because as we saw in the EDA part, the price of the detached housing is generally higher than the price of the other housings. It does not explain the full difference but at least help to understand it a bit better. Let’s look at the distribution of prices by type of housing in the most and least deprived areas to have a really clear view:

IMD decile	Housing tpe	1st quantile	Median price	mean price	3rd quantile
1	D	160000	199950	220842	250000
1	F	72000	105795	157357	165000
1	O	70000	150000	573441	375000
1	S	99500	130000	139625	165995
1	T	65000	90000	107731	135000
10	D	329950	438000	536146	615000
10	F	170000	240000	308310	335000
10	O	150000	375000	1263185	820000
10	S	232500	315000	362471	425000
10	T	214000	287500	348976	395000

Although at first we could have though that the price link seen at the question 2 was due to the different type of housing we just looked at, it seems that by looking at this table, that part of this difference is coming more from the other types of housings where the prices have way bigger differences than the detached houses ones.

To conclude this question. We do have different “housing consumption” depending on the level of deprivation from the people which was quite logic in some way but it helps understanding more about the market.

4th question : “Are we building more in the less deprived area or in the most deprived?”

To answer this question we need to visualize the number of new building sold by IMD decile:

IMD decile	New or old	Count
1	Y	7752
2	Y	9662
3	Y	11547
4	Y	10308
5	Y	13139
6	Y	13746
7	Y	14065
8	Y	14875
9	Y	13348
10	Y	14392

Here we can clearly see that the majority of newly built housings are done in “mediumly” to lightly deprived areas since decile 5 to 10 have nearly all 2 times more newly built housing that were sold compared to the decile 1 which is the most deprived where there is quite a lot less new developments or at least it seems to be the case in the number of sales. This is logic in the way that those regions generally have way less money available but we could have thought that many developers would try to profit from those areas to transform them into better places and modify the city to make it look cleaner. This does not seem to happen and developers are or at least seemed to have played it quite safely by developing mainly into less deprived area that are looking better in the eyes of the buyers.

Conclusion

This project was a great chance offered by the professor to work for the first time of my life on such a scale. It was quite challenging but very rewarding in terms of knowledge and understanding. It made me realize hat working with large dataset is really hard and even when they are properly cleaned we need to be aware that each thing we want to do may take quite some times, especially in my case with my 5 years old PC which, to be honest feel to be slower and slower especially when I was asking him to plot a million points on a graphic. This project made me more confident in my use of R and helped me quite a lot in learning this tool. And hopefully will help me pushing even further in the subject. I sadly did not find the time to try to do some modelisation but with the data I had this would have surely not brought that much since the few variables I had to try to predict the prices were not explaining enough of it to have something really precise.

About the results now, to be honest I was at first awaiting a bit more from the regression around the different variables. Now that I had the possibility to look at it it seems clear why they do not explain as much as I was hoping since in realty the major factors that guides the pricing of real estate are the size and built quality of them and the surrounding area is more or less the cherry on the cake. Although I still believe that those data could be used in modeling the market in a more precise way.

About limitations, the main issue of this work is the fact that we are only looking at one year, meaning that to be sure about the links we should look at them over the course of a larger period of time. This could be part of future research as well as doing for instance a more precise analysis of the crime levels ad which crimes affect the most the prices to be able to control this since crimes can go from “simple” harassment up to physical violence which would certainly not have the same effect on the prices.

Appendix

In this section I’ll show and explain the code to create the map. For this map I used some shapefiles coming from https://borders.ukdataservice.ac.uk/ukborders/easy_download/prebuilt/shape/England_lsoa_2011_sgen_clipped.zip we are using the full file without any reduction which gives the most precision in the output.

I first load the datas from the IMD and tidy them again, since the code is coming before the data section I need to do this otherwise there would be an issue.

#check appendix to understand the code
IMD <-
  read.csv(here::here("data/Domains_of_Deprivation_by_LSOA.csv"))
IMD <- as_tibble(IMD)
IMD <- IMD %>%
  rename(
    LSOA_code =  ï..LSOA.code..2011.,
    LSOA_name = LSOA.name..2011.,
    IMD_rank = Index.of.Multiple.Deprivation..IMD..Rank..where.1.is.most.deprived.,
    IMD_decile = Index.of.Multiple.Deprivation..IMD..Decile..where.1.is.most.deprived.10..of.LSOAs.,
    Income_rank = Income.Rank..where.1.is.most.deprived.,
    Income_decile = Income.Decile..where.1.is.most.deprived.10..of.LSOAs.,
    Employment_rank = Employment.Rank..where.1.is.most.deprived.,
    Employment_decile = Employment.Decile..where.1.is.most.deprived.10..of.LSOAs.,
    Crime_rank = Crime.Rank..where.1.is.most.deprived.,
    Crime_decile = Crime.Decile..where.1.is.most.deprived.10..of.LSOAs.,
    Living_Environment_rank = Living.Environment.Rank..where.1.is.most.deprived.,
    Living_Environment_Decile = Living.Environment.Decile..where.1.is.most.deprived.10..of.LSOAs.,
    Health_Deprivation_rank = Health.Deprivation.and.Disability.Rank..where.1.is.most.deprived.,
    Health_Deprivation_decile = Health.Deprivation.and.Disability.Decile..where.1.is.most.deprived.10..of.LSOAs.,
    Local_Authority_Name = Local.Authority.District.name..2019.,
    Skill_rank = Education..Skills.and.Training.Rank..where.1.is.most.deprived.,
    Skill_decile = Education..Skills.and.Training.Decile..where.1.is.most.deprived.10..of.LSOAs.,
    Barrier_to_Housing_Rank = Barriers.to.Housing.and.Services.Rank..where.1.is.most.deprived.,
    Barrier_to_Housing_Decile = Barriers.to.Housing.and.Services.Decile..where.1.is.most.deprived.10..of.LSOAs.,
    Local_Authority_code = Local.Authority.District.code..2019.
  )
IMD_tidy <- IMD %>%
  select(
    LSOA_code,
    LSOA_name,
    IMD_rank,
    IMD_decile,
    Income_rank,
    Income_decile,
    Employment_rank,
    Employment_decile,
    Crime_rank,
    Crime_decile,
    Health_Deprivation_rank,
    Health_Deprivation_decile,
    Skill_rank,
    Skill_decile
  )%>%
  #deleting spaces to avoir creation of NA for the next part
  mutate(IMD_rank = gsub(" ", "", IMD_rank),
         IMD_decile = gsub(" ", "", IMD_decile),
         Income_rank = gsub(" ", "", Income_rank),
         Income_decile = gsub(" ", "", Income_decile),
         Employment_rank = gsub(" ", "", Employment_rank),
         Employment_decile = gsub(" ", "", Employment_decile),
         Crime_rank = gsub(" ", "", Crime_rank),
         Crime_decile = gsub(" ", "", Crime_decile),
         Health_Deprivation_rank = gsub(" ", "", Health_Deprivation_rank),
         Health_Deprivation_decile = gsub(" ", "", Health_Deprivation_decile),
         Skill_rank = gsub(" ", "", Skill_rank),
         Skill_decile = gsub(" ", "", Skill_decile)
  )%>%
  #transforming numbers into the right class, from character to integers
  mutate(
    IMD_rank = as.integer(IMD_rank),
    IMD_decile = as.integer(IMD_decile),
    Income_rank= as.integer(Income_rank),
    Income_decile = as.integer(Income_decile),
    Employment_rank = as.integer(Employment_rank),
    Employment_decile = as.integer(Employment_decile),
    Crime_rank = as.integer(Crime_rank),
    Crime_decile = as.integer(Crime_decile),
    Health_Deprivation_rank = as.integer(Health_Deprivation_rank),
    Health_Deprivation_decile = as.integer(Health_Deprivation_decile),
    Skill_rank = as.integer(Skill_rank),
    Skill_decile = as.integer(Skill_decile)
  )

Once the Data is tidy, I need to select only what I will truly be using therefore I am taking only the code and the IMD_decile from the table since those are the only things needed to respectively link the table and then fill the map to visualize the data.

IMD_map <- IMD_tidy %>%
  rename(code = LSOA_code)%>%
  select(code,
         IMD_decile)%>%
  mutate(code = gsub(" ", "", code))

Once the data is ready we need to use 2 new libraries, SF which is used to read and manipulate the shapefile and tmap which will be use to create the map:

library(sf)
library(tmap)

Once the libraries are loaded we will use the function st_read from the sf package to read the shapefile which will enable us to work with it:

data<-st_read(here::here("Map/england_lsoa_2011_sgen_clipped.shp"))

Now that we are able to work with the shapefile, we are going to join the IMD table that we tidied earlier on to be able to plot latter:

full_map <- left_join(data, IMD_map, by ="code")

Then we add the styling we want for the map by using tmap_style:

tmap_style("cobalt")

And finally we use the qtm function that is doing a “Quick Thematic Map Plot” for us: and we have our nice map done.

qtm(full_map, fill = "IMD_decile", border = NULL)

At first I wanted to add the tmap_mode("view") function that should make the plot interactive but it seems that it does not work with what I have done, not surre about why.